title: Handmade pixels: Exposing the animation process

authors: Perrott, Lisa

abstract: Handmade Pixels seeks to expose those aspects of the animation process that are often relegated to ‘behind the scenes’ archives, ‘making of’ videos, or even discarded as rubbish. It aims to celebrate the distinctive approach of artists who experiment with diverse methods and techniques.
Many of the items selected here are quite different from the works typically exhibited in art galleries. Process materials such as working sketches and storyboards are rarely displayed as works of art in their own right. They are often archived or disposed of once the final film has been completed. These materials should be exhibited – not least because they communicate the creative genius and idiosyncratic craftwork of an animator.

text: Handmade pixels: Exposing the animation process Handmade Pixels seeks to expose those aspects of the animation process that are often relegated to ‘behind the scenes’ archives, ‘making of’ videos, or even discarded as rubbish. It aims to celebrate the distinctive approach of artists who experiment with diverse methods and techniques.
Many of the items selected here are quite different from the works typically exhibited in art galleries. Process materials such as working sketches and storyboards are rarely displayed as works of art in their own right. They are often archived or disposed of once the final film has been completed. These materials should be exhibited – not least because they communicate the creative genius and idiosyncratic craftwork of an animator.

year: 2011

title: Evaluation of deep learning techniques on a novel hierarchical surgical tool dataset

authors: Rodrigues, Mark William

subjects: Science & Technology

abstract: A new hierarchically organised dataset for artificial intelligence and machine learning research is presented, focusing on intelligent management of surgical tools. In addition to 360 surgical tool classes, we create a four level hierarchical structure for our dataset defined by 2 specialities, 12 packs and 35 sets. We employ different convolutional neural network training strategies to evaluate image classification and retrieval performance on this dataset, including the utilisation of prior information in the form of a taxonomic hierarchy tree structure. We evaluate the effects of image size and the number of images per class on model predictive performance. Experiments with the mapping of image features and class embeddings in semantic space using measures of semantic similarity between classes show that providing prior information results in a significant improvement in image retrieval performance on our dataset.

text: Evaluation of deep learning techniques on a novel hierarchical surgical tool dataset A new hierarchically organised dataset for artificial intelligence and machine learning research is presented, focusing on intelligent management of surgical tools. In addition to 360 surgical tool classes, we create a four level hierarchical structure for our dataset defined by 2 specialities, 12 packs and 35 sets. We employ different convolutional neural network training strategies to evaluate image classification and retrieval performance on this dataset, including the utilisation of prior information in the form of a taxonomic hierarchy tree structure. We evaluate the effects of image size and the number of images per class on model predictive performance. Experiments with the mapping of image features and class embeddings in semantic space using measures of semantic similarity between classes show that providing prior information results in a significant improvement in image retrieval performance on our dataset.

year: 2022

title: Takuahi: Te oriori mō Tāmaunga-o-te-rangi - Mana atua, mana whenua, mana tangata

authors: Dewes, Mahue

subjects: Takuahi

abstract: E roa nei tātau te Māori nō ngā wā o Hawaiki e tito ana i te waiata, i te haka, i te oriori, i te mōteatea hei waka kawe i ngā kōrero tuku iho ki ngā whakatipuranga hou. He putuputu tonu ngā tūmomo karere, ka raua atu ki roto i wēnei momo titonga waiata a te Māori. Ka whārikihia e ngā tohunga kaitito ngā karere nei mā te reo kīwaha, mā te reo whakataukī, mā te reo auaha hei kura huna. Mei māmā te kimi, ka tohunga katoa ngā Māori. Kai te aroaro o te tuhingaroa nei, ka ketuketu i tētahi o ngā oriori o Ngāti Porou, otiā, nō Te Whānau-a-Hinerupe, ko te oriori mō Tāmaunga-o-te-rangi, nā Te Māperetahi. Mā konei ake e ruku atu ai ki te raparapa i ngā kura huna e whakatauira ana i te mana Atua, mana whenua, mana tangata hei mana ahi kā. Mā tēnā hoki e whakatauira te mana ahi kā, kai a Tama, otiā, hei tauira atu ki ngā uri o Te Whānau-a-Hinerupe i tō rātau ake ahi kā roa ki Te Kawakawa mai Tawhiti. Ko ngā kōrero kua kohingia, he kōrero nō ngā tāngata e mōhio ana ki ngā tūmomo mana, ā, ki ngā kōrero e pā ana ki te oriori nei. Ka iringia wēnei rau kōrero hei whakarākei tonu i te pae tapu o Te Whānau-a-Hinerupe.

text: Takuahi: Te oriori mō Tāmaunga-o-te-rangi - Mana atua, mana whenua, mana tangata E roa nei tātau te Māori nō ngā wā o Hawaiki e tito ana i te waiata, i te haka, i te oriori, i te mōteatea hei waka kawe i ngā kōrero tuku iho ki ngā whakatipuranga hou. He putuputu tonu ngā tūmomo karere, ka raua atu ki roto i wēnei momo titonga waiata a te Māori. Ka whārikihia e ngā tohunga kaitito ngā karere nei mā te reo kīwaha, mā te reo whakataukī, mā te reo auaha hei kura huna. Mei māmā te kimi, ka tohunga katoa ngā Māori. Kai te aroaro o te tuhingaroa nei, ka ketuketu i tētahi o ngā oriori o Ngāti Porou, otiā, nō Te Whānau-a-Hinerupe, ko te oriori mō Tāmaunga-o-te-rangi, nā Te Māperetahi. Mā konei ake e ruku atu ai ki te raparapa i ngā kura huna e whakatauira ana i te mana Atua, mana whenua, mana tangata hei mana ahi kā. Mā tēnā hoki e whakatauira te mana ahi kā, kai a Tama, otiā, hei tauira atu ki ngā uri o Te Whānau-a-Hinerupe i tō rātau ake ahi kā roa ki Te Kawakawa mai Tawhiti. Ko ngā kōrero kua kohingia, he kōrero nō ngā tāngata e mōhio ana ki ngā tūmomo mana, ā, ki ngā kōrero e pā ana ki te oriori nei. Ka iringia wēnei rau kōrero hei whakarākei tonu i te pae tapu o Te Whānau-a-Hinerupe.

year: 2016