cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.15258589
title: Trade-off Analysis of Classical Machine Leaning and Deep Learning Models for Robust Brain Tumor Detection: A Benchmark Study

description: Paper:

Trade-off Analysis of Classical Machine Leaning and Deep Learning Models for Robust Brain Tumor Detection: A Benchmark Study.

 

Code details: 

Please see the GitHub repository for code and usage instructions: 

https://github.com/yangzi334/BrainTumorClassification

 

Uploaded Contents in Zenodo:

- Primary



The primary raw dataset (Brain tumor data.rar)

Cleaned primary raw dataset (brain tumor binary data.zip)

After splitting 'cleaned primary raw dataset' with ratio 0.7, 0.15, 0.15,  'train.zip', 'validataion.zip', 'test.zip' were generated.


- Cross-Dataset



Cross-domain raw data (brain tumor cross-domain data.zip)

Cleaned Cross-domain  (brain tumor cross-domain binary data.zip)


Note: In the data preprocessing step, before we generated 'brain tumor external data.zip' , we first used phash alogrithm to compare total images from cross-domain source data (brain tumor external raw.zip) against training images from the primary data (train_folder.zip), any visually identical or nearly identical images will be removed from the cross-dataset. The details can be found in the 'check image leakage.ipynb' in the GitHub. 

 

Training models:

SVN_HOG_new.zip



best_svm_hog_model.pkl — Final support vector machine (SVM) model trained with HOG features. 


 

ResNet18.zip



best_resnet18_overall.pth — Final fine-tuned resnet18 model weights with best overall validation performance.

best_resnet18_run1.pth — Best checkpoint for resnet18 from run 1.

best_resnet18_run2.pth — Best checkpoint for resnet18 from run 2.

best_resnet18_run3.pth — Best checkpoint for resnet18 from run 3.


 

Vit_B_16_new.zip





best_vit_overall.pth — Final fine-tuned ViT-B/16 model weights with best overall validation performance.




best_vit_run1.pth — Best checkpoint for ViT-B/16 from run 1.




best_vit_run2.pth — Best checkpoint for ViT-B/16 from run 2.




best_vit_run3.pth — Best checkpoint for ViT-B/16 from run 3.



 

SimCLR.zip



best_simclr_overall.pth — Final fine-tuned simclr model weights with best overall validation performance.

best_simclr_run1.pth — Best checkpoint for simclr from run 1.

best_simclr_run2.pth — Best checkpoint for simclr from run 2.

best_simclr_run3.pth — Best checkpoint for simclr from run 3.

best_simclr_encoder_only.pth — SimCLR encoder weights only (trained with contrastive learning, no classifier head). Can be used for downstream tasks
DOI: 10.5281/zenodo.17066339
title: Trade-off Analysis of Classical Machine Leaning and Deep Learning Models for Robust Brain Tumor Detection: A Benchmark Study

description: Paper:

Trade-off Analysis of Classical Machine Leaning and Deep Learning Models for Robust Brain Tumor Detection: A Benchmark Study.

 

Code details: 

Please see the GitHub repository for code and usage instructions: 

https://github.com/yangzi334/BrainTumorClassification

 

Uploaded Contents in Zenodo:

- Primary



The primary raw dataset (Brain tumor data.rar)

Cleaned primary raw dataset (brain tumor binary data.zip)

After splitting 'cleaned primary raw dataset' with ratio 0.7, 0.15, 0.15,  'train.zip', 'validataion.zip', 'test.zip' were generated.


- Cross-Dataset



Cross-domain raw data (brain tumor cross-domain data.zip)

Cleaned Cross-domain  (brain tumor cross-domain binary data.zip)


Note: In the data preprocessing step, before we generated 'brain tumor external data.zip' , we first used phash alogrithm to compare total images from cross-domain source data (brain tumor external raw.zip) against training images from the primary data (train_folder.zip), any visually identical or nearly identical images will be removed from the cross-dataset. The details can be found in the 'check image leakage.ipynb' in the GitHub. 

 

Training models:

SVN_HOG_new.zip



best_svm_hog_model.pkl — Final support vector machine (SVM) model trained with HOG features. 


 

ResNet18.zip



best_resnet18_overall.pth — Final fine-tuned resnet18 model weights with best overall validation performance.

best_resnet18_run1.pth — Best checkpoint for resnet18 from run 1.

best_resnet18_run2.pth — Best checkpoint for resnet18 from run 2.

best_resnet18_run3.pth — Best checkpoint for resnet18 from run 3.


 

Vit_B_16_new.zip





best_vit_overall.pth — Final fine-tuned ViT-B/16 model weights with best overall validation performance.




best_vit_run1.pth — Best checkpoint for ViT-B/16 from run 1.




best_vit_run2.pth — Best checkpoint for ViT-B/16 from run 2.




best_vit_run3.pth — Best checkpoint for ViT-B/16 from run 3.



 

SimCLR.zip



best_simclr_overall.pth — Final fine-tuned simclr model weights with best overall validation performance.

best_simclr_run1.pth — Best checkpoint for simclr from run 1.

best_simclr_run2.pth — Best checkpoint for simclr from run 2.

best_simclr_run3.pth — Best checkpoint for simclr from run 3.

best_simclr_encoder_only.pth — SimCLR encoder weights only (trained with contrastive learning, no classifier head). Can be used for downstream tasks
DOI: 10.15468/dl.ztrqmv
title: Occurrence Download

description: A dataset containing 37 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "GadmGid is CHN.28_1",
 "TaxonKey is Kobresia humilis"
 ]
}

 The dataset includes 37 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0035730-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2zyubh
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Portunus segnis",
 "Country is Tunisia",
 "HasCoordinate is true"
 ]
}

 The dataset includes 3 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0035732-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4qpb8u
title: Occurrence Download

description: A dataset containing 20 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "GadmGid is CHN.28_1",
 "TaxonKey is Acantholimon tianschanicum"
 ]
}

 The dataset includes 20 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0035731-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4k2sck
title: Occurrence Download

description: A dataset containing 388 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Issue is one of (Coordinate rounded, Geodetic datum invalid, Geodetic datum assumed WGS84, Coordinate reprojected, Coordinate reprojection failed, Coordinate reprojection suspicious, Coordinate accuracy invalid, Coordinate precision/uncertainty mismatch, Footprint SRS invalid, Footprint WKT invalid, Country mismatch, Country invalid, Country derived from coordinates, Continent coordinate mismatch, Continent country mismatch, Continent invalid, Continent derived from country, Continent derived from coordinates, Presumed swapped coordinate, Presumed negated longitude, Presumed negated latitude, Recorded date unlikely, Taxon match aggregate, The scientific name ID was not used in backbone matching, The taxon concept ID was not used in backbone matching, The taxon ID was not used in backbone matching, The scientific name ID was not found in the checklist, The taxon concept ID was not found in the checklist, The taxon ID was not found in the checklist, The scientific name differs on the record from that found in the checklist, Taxon match none, The backbone match found using the taxon IDs differs from what would be found if using the scientific names, Depth not metric, Depth unlikely, Depth min max swapped, Depth non numeric, Elevation unlikely, Elevation min max swapped, Elevation not metric, Elevation non numeric, Modified date invalid, Modified date unlikely, Identified date unlikely, Identified date invalid, Basis of record invalid, Type status invalid, Multimedia date invalid, Multimedia URI invalid, References URI invalid, Error during interpretation, Individual count invalid, Individual count conflicts with occurrence status, Occurrence status unparsable, Occurrence status inferred from individual count, Occurrence status inferred from basis of record, Georeferenced date unlikely, Georeferenced date invalid, Ambiguous institution, Ambiguous collection, Institution match none, Collection match none, Institution match fuzzy, Collection match fuzzy, Institution collection mismatch, Possibly on loan, Different owner institution)",
 "OccurrenceStatus is Present",
 "TaxonKey is Laticilla burnesii"
 ]
}

 The dataset includes 388 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0035733-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.uu2skp
title: Occurrence Download

description: A dataset containing 2681 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Gomphocarpus cancellatus",
 "Country is Australia",
 "HasCoordinate is true"
 ]
}

 The dataset includes 2681 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0035734-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.n32qvs
title: Occurrence Download

description: A dataset containing 5 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Creagrutus hysginus)",
 "BasisOfRecord is one of (Specimen, Literature Occurrence, Human Observation, Observation)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1991",
 "Year is less than or equal to 2025"
 ]
}

 The dataset includes 5 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0035735-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jctts2
title: Occurrence Download

description: A dataset containing 504 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Parailia pellucida, Parailia somalensis, Parailia spiniserrata, Pareutropius buffei, Pareutropius debauwi, Pareutropius longifilis, Pareutropius mandevillei, Schilbe angolensis, Schilbe banguelensis, Schilbe bocagii, Schilbe brevianalis, Schilbe congensis, Schilbe djeremi, Schilbe grenfelli, Schilbe intermedius, Schilbe laticeps, Schilbe mandibularis, Schilbe marmoratus, Schilbe micropogon, Schilbe moebiusii, Schilbe multitaeniatus, Schilbe mystus, Schilbe nyongensis, Schilbe tumbanus, Schilbe uranoscopus, Schilbe yangambianus, Schilbe zairensis, Siluranodon auritus, Macrognathus keithi, Mastacembelus albomaculatus, Mastacembelus ansorgii, Mastacembelus aviceps, Mastacembelus brachyrhinus, Mastacembelus brichardi, Mastacembelus congicus, Mastacembelus crassus, Mastacembelus cryptacanthus, Mastacembelus cunningtoni, Mastacembelus ellipsifer, Mastacembelus flavidus, Mastacembelus flavomarginatus, Mastacembelus niger, Mastacembelus frenatus, Mastacembelus greshoffi, Mastacembelus latens, Mastacembelus liberiensis, Mastacembelus loennbergii, Mastacembelus micropectus, Mastacembelus moorii, Mastacembelus nigromarginatus, Mastacembelus ophidium, Mastacembelus paucispinis, Mastacembelus plagiostomus, Mastacembelus platysoma, Mastacembelus praensis, Mastacembelus robertsi, Mastacembelus sanagali, Mastacembelus seiteri, Mastacembelus sexdecimspinus, Mastacembelus shiloangoensis, Mastacembelus shiranus, Mastacembelus taiaensis, Mastacembelus tanganicae, Mastacembelus traversi, Mastacembelus vanderwaali, Mastacembelus zebratus, Monopterus boueti, Ophisternon afrum, Enneacampus ansorgii, Enneacampus kaupi, Hippichthys cyanospilos, Hippichthys heptagonus, Hippichthys spicifer, Microphis aculeatus, Microphis argulus, Microphis brachyurus, Microphis brachyurus aculeatus, Microphis fluviatilis, Microphis leiaspis, Syngnathus abaster, Auriglobus modestus, Chelonodontops patoca, Tetraodon duboisi, Tetraodon lineatus, Tetraodon mbu, Tetraodon miurus, Tetraodon pustulatus, Tetraodon schoutedeni, Altolamprologus fasciatus, Haplochromis bloyeti, Haplochromis desfontainii, Haplochromis luluae, Haplochromis oligacanthus, Haplochromis polli, Haplochromis tweddlei, Labeo fuelleborni, Labeo rocadasi, Metriaclima pulpican, Protomelas ornatus, Salarias fluviatilis)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Specimen, Observation, Human Observation, Machine Observation, Material sample, Literature Occurrence, Material citation, Occurrence evidence)",
 "Geometry POLYGON ((37.1382 -6.9401,28.1382 -6.9401,28.1382 -15.9401,37.1382 -15.9401,37.1382 -6.9401))"
 ]
}

 The dataset includes 504 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0035736-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nfnygw
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Eriocheir japonica",
 "Country is United States of America",
 "HasCoordinate is true"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0035737-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.pfxns7
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Hoya serpens",
 "Country is Australia",
 "HasCoordinate is true"
 ]
}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0035739-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17068598
title: Dataset of KALFormer project

description: About this directory:











ETT-SmallDescription: This dataset is part of the ETT (Electricity Transformer Temperature) dataset, which typically involves time series data collected from electric transformers for monitoring and forecasting. The "小型" (Small) version likely contains a smaller subset of data that could be used for quick model testing or experimentation.




time_stamp.npyDescription: This file likely contains timestamp data for the time series datasets. .npy is a binary file format used by NumPy to store arrays. It could include the corresponding time steps for each data point in the various time series datasets.




V_228.csvDescription: This dataset is likely related to a specific variable, possibly an energy variable (e.g., voltage, or another relevant feature for forecasting tasks). It is stored in CSV format, with 72.23 terabytes of data, which is quite large and could represent a high-resolution time series.




W_228.csvDescription: Similar to "V_228.csv", this dataset seems to be another time series related to a different variable, perhaps weather-related data (e.g., wind speed, weather events). The file is comparatively smaller than "V_228.csv".




electricity.csvDescription: This dataset likely contains time series data related to electricity consumption or generation. It is a well-known dataset in the domain of energy forecasting, often used to predict demand or optimize energy usage.




traffic.csvDescription: This dataset could involve time series data on traffic flow, congestion, or related metrics, often used in smart city projects or transportation management systems. It has a large amount of data (136.48 TB), indicating a high resolution or long time span for the traffic data.




weather.csvDescription: This dataset likely contains time series data related to weather conditions, such as temperature, humidity, wind speed, or other meteorological factors. It's essential for applications like weather forecasting or climate analysis.
DOI: 10.5281/zenodo.17068599
title: Dataset of KALFormer project

description: About this directory:











ETT-SmallDescription: This dataset is part of the ETT (Electricity Transformer Temperature) dataset, which typically involves time series data collected from electric transformers for monitoring and forecasting. The "小型" (Small) version likely contains a smaller subset of data that could be used for quick model testing or experimentation.




time_stamp.npyDescription: This file likely contains timestamp data for the time series datasets. .npy is a binary file format used by NumPy to store arrays. It could include the corresponding time steps for each data point in the various time series datasets.




V_228.csvDescription: This dataset is likely related to a specific variable, possibly an energy variable (e.g., voltage, or another relevant feature for forecasting tasks). It is stored in CSV format, with 72.23 terabytes of data, which is quite large and could represent a high-resolution time series.




W_228.csvDescription: Similar to "V_228.csv", this dataset seems to be another time series related to a different variable, perhaps weather-related data (e.g., wind speed, weather events). The file is comparatively smaller than "V_228.csv".




electricity.csvDescription: This dataset likely contains time series data related to electricity consumption or generation. It is a well-known dataset in the domain of energy forecasting, often used to predict demand or optimize energy usage.




traffic.csvDescription: This dataset could involve time series data on traffic flow, congestion, or related metrics, often used in smart city projects or transportation management systems. It has a large amount of data (136.48 TB), indicating a high resolution or long time span for the traffic data.




weather.csvDescription: This dataset likely contains time series data related to weather conditions, such as temperature, humidity, wind speed, or other meteorological factors. It's essential for applications like weather forecasting or climate analysis.
DOI: 10.15468/dl.75628x
title: Occurrence Download

description: A dataset containing 85791 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "TaxonKey is Caudata"
 ]
}

 The dataset includes 85791 records from 141 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013776-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fxujef
title: Occurrence Download

description: A dataset containing 56893 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is one of (Paspalum dilatatum Poir.)"
 ]
}

 The dataset includes 56893 records from 988 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013784-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bh4u95
title: Occurrence Download

description: A dataset listing the 1400 species recorded in GBIF matching the query:
{
 "and" : [
 "GadmGid is one of (BRA.11.26_2, BRA.11.48_2)",
 "TaxonKey is Chordata"
 ]
}

 The dataset's 1400 records were derived from 71 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013773-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5066/p15x44rs
title: Estimated Annual Recharge to the Edwards Aquifer in the San Antonio Area, by Stream Basin or Ungaged Area, 1934–2023

description: The Edwards aquifer in south-central Texas is one of the most permeable and productive aquifers in the United States and is the major source of public water supply for Bexar, Comal, Hays, Medina, and Uvalde Counties. The Edwards aquifer also supplies large quantities of water for use in agriculture, business, and industry in the region. The major artesian springs of the Edwards aquifer provide water for recreational activities, businesses, and downstream users, and provide habitat for several threatened or endangered species.

The areas pertinent to the recharge process are the catchment area and the recharge zone. The catchment area consists of the parts of river basins upstream from the recharge zone. Streams in the catchment area generally gain water as they flow toward the recharge zone. As the streams flow across the recharge zone, which is essentially the outcrop of the Edwards aquifer, they lose substantial amounts of water through infiltration into the highly permeable, faulted and fractured rocks of the outcrop. Direct infiltration of rainfall also occurs in the interstream areas within the recharge zone.

Annual recharge estimates are based on data collected from a network of U.S. Geological Survey (USGS) streamflow-gaging stations at sites upstream and downstream from the recharge zone and on assumptions related to applying runoff characteristics from gaged areas to ungaged areas, Puente (1978). Runoff is affected by the distribution of rainfall, which historically has been estimated from a network of rain gages, some operated by the USGS, some by the Edwards Aquifer Authority (EAA), and some by the National Weather Service. Since 2004, the distribution of rainfall has been estimated from calibrated NEXRAD (NEXt-generation weather RADar) data provided by the EAA.

The annual estimation of recharge to the Edwards aquifer is part of a continuing program of the USGS in cooperation with the Edwards Aquifer Authority. This data release is formatted as a tab-delimited file (.txt) that contains the estimated annual recharge to the Edwards aquifer for 1934 through 2023. The estimated annual recharge is divided into eight major river basins within the catchment area and for some of those basins will also include estimates of recharge from adjacent ungagged areas.
DOI: 10.15468/dl.nh6hf6
title: Occurrence Download

description: A dataset containing 1609 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is one of (Paspalum fimbriatum Kunth)"
 ]
}

 The dataset includes 1609 records from 146 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013788-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2wvyh6
title: Occurrence Download

description: A dataset containing 1173 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is one of (Paspalum lineare Trin.)"
 ]
}

 The dataset includes 1173 records from 98 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013790-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.