ηϚϯςΟοΫηάϝϯςʔγϣϯʹΑΔ௒ߴղ૾౓ը૾͔ΒͷมԽ఺‫ݕ‬ग़ʹؔ͢Δ‫ڀݚ‬ࢦಋ‫ڭ‬तɿࢁԼོٛ

TP19015 ౵Ҫॣ‫ޗ‬

2. มԽ఺‫ݕ‬ग़ͷैདྷ๏CNN Λ༻͍ͨมԽ఺‫ݕ‬ग़๏͸ɼಛ௃ྔϕʔεͱֶशϕʔεͷ 2 ͭͷΞϓϩʔνʹ෼ྨͰ͖Δɽಛ௃ྔϕʔεͷมԽ఺‫ݕ‬ग़๏ɿCNN ΑΓநग़ͨ͠ 2 ຕͷಛ௃Ϛοϓͷ‫͔ࢉܭ཭ڑ‬ΒมԽྖҬΛਪఆ͢ΔɽͦͷͨΊɼมԽ఺‫ݕ‬ग़ͷͨΊͷֶशσʔληοτΛඞཁͱ͠ͳ͍ɽಛ௃ྔϕʔεͷ୅දతͳख๏Ͱ͋Δ CNNF-F[1] ͸ɼImageNetͰࣄલֶशͨ͠ VGG19 Λ༻͍ͯɼը૾ϖΞ͔Βಛ௃Ϛοϓநग़͠มԽྖҬΛ‫ݕ‬ग़͢Δɽ‫ݕ‬ग़ʹ͸ϢʔΫϦου‫཭ڑ‬Λ࢖༻͠ɼมԽྖҬΛܾఆ͢ΔͨΊʹᮢ஋ॲཧΛࢪ͢ɽมԽྖҬͷΈΛ‫ݕ‬ग़͢Δख๏Ͱ͋ΔͨΊɼมԽྖҬʹଐੑΛ෇༩͢Δ͜ͱ͕Ͱ͖ͳ͍ɽֶशϕʔεͷมԽ఺‫ݕ‬ग़๏ɿมԽ఺‫ݕ‬ग़ͷͨΊͷσʔληοτΛ༻͍ͯը૾ؒͷྨࣅੑ (ඇྨࣅੑ) Λֶश͢ΔͨΊɼલड़ͷΞϓϩʔνͱൺ΂ͯࢹ఺ͷͣΕʹ‫ݕͳ݈ؤ‬ग़͕ՄೳͰ͋Δɽֶशϕʔεͷ୅දతͳख๏Ͱ͋Δ FC-EF-Res[2] ͸ɼมԽ఺‫ݕ‬ग़λεΫͱηϚϯςΟοΫηάϝϯςʔγϣϯλεΫΛͦΕͧΕผʑͷωοτϫʔΫͰॲཧ͠ɼͦͷ݁ՌΛ౷߹͢Δख๏Ͱ͋Δɽ̎ͭͷωοτϫʔΫ͸ U-Net[3] Λϕʔεʹߏ੒͞Εɼ࢒ࠩϒϩοΫΛಋೖ͍ͯ͠ΔɽηάϝϯςʔγϣϯωοτϫʔΫ͔Βநग़ͨ͠ಛ௃Ϛοϓͷࠩ෼ΛɼมԽ఺‫ݕ‬ग़ωοτϫʔΫʹεΩοϓ઀ଓ͢Δ͜ͱͰɼը૾ؒͷ໌ࣔతͳൺֱΛߦ͍ͳ͕Βֶश͢Δɽ͔͠͠ɼλεΫ͝ͱʹಠཱͨ͠ωοτϫʔΫΛ༻͍ΔͨΊɼֶशதʹλεΫؒͰ৘ใΛ૬‫ޓ‬ར༻͢Δ͜ͱ͕Ͱ͖ͳ͍ͱ͍͏໰୊͕͋Δɽ

3. ఏҊख๏ຊ‫Ͱڀݚ‬͸ɼมԽྖҬͱΦϒδΣΫτΫϥεΛಉ࣌ʹਪఆ͢Δ͜ͱ͕Ͱ͖ΔมԽ఺‫ݕ‬ग़๏ΛఏҊ͢ΔɽఏҊख๏ͷωοτϫʔΫߏ଄Λਤ 1 ʹࣔ͢. ωοτϫʔΫ͸ɼEncoderDecoder ߏ଄Λ࣋ͭ̎ͭͷϞσϧ͔Βߏ੒͞Ε͓ͯΓɼมԽ఺‫ݕ‬ग़Ϟσϧʹ͸ηάϝϯςʔγϣϯϞσϧͷ࠷ऴ૚͔Βநग़ͨ͠ಛ௃ϚοϓΛೖྗ͢Δɽ

3.1 ηάϝϯςʔγϣϯϞσϧηάϝϯςʔγϣϯϞσϧ͸ɼU-Net Λϕʔεͱ͢ΔωοτϫʔΫߏ଄Ͱ͋Δɽը૾ϖΞͷͦΕͧΕΛ‫ݸ‬ผʹωοτϫʔΫ΁ೖྗ͢Δɽͳ͓ɼ֤ωοτϫʔΫͷॏΈ͸‫ڞ‬༗͍ͯ͠ΔɽηάϝϯςʔγϣϯϞσϧͷଛࣦؔ਺͸ɼैདྷͷ
U-Net ͱಉ༷ɼΫϩεΤϯτϩϐʔଛࣦΛ࢖༻͢Δɽ

3.2 มԽ఺‫ݕ‬ग़ϞσϧมԽ఺‫ݕ‬ग़Ϟσϧ͸ɼ̎ͭͷ Encoder ͱ 1 ͭͷ DecoderͰߏ੒ͨ͠ωοτϫʔΫߏ଄ͱͳ͓ͬͯΓɼͦΕͧΕ 3 ૚ͷ৞ΈࠐΈ૚Λ࣋ͭɽ2 ͭͷ Encoder ʹΑΓɼը૾ؒͰҟͳΔಛ௃Λ֫ಘ͢Δ͜ͱ͕ՄೳͰ͋Δɽ·ͨɼ֤ Encoderʹ͸ηάϝϯςʔγϣϯϞσϧΑΓಘΒΕͨಛ௃ϚοϓΛͦΕͧΕೖྗ͠ɼDecoder ʹ͸֤ Encoder ΑΓಘΒΕͨಛ௃ϚοϓΛνϟϯωϧํ޲ʹ࿈݁͠ೖྗ͢Δɽ

image (past)

softmax

Segmentation (past)weight share

Change detection
image (present)

Change detection model !$%Segmentation model !!"#softmaxมԽ఺‫ݕ‬ग़͸ɼҟͳΔ࣌ࠁʹࡱӨ͞ΕͨಉҰγʔϯը૾͔ΒมԽͨ͠ྖҬΛநग़͢Δ໰୊Ͱ͋ΔɽCNN Λ༻͍ͨมԽ఺‫ݕ‬ग़๏ [1][2] ͸ɼҐஔͣΕ΍‫ڥ؀‬มԽʹ‫͋Ͱ݈ؤ‬ΔͨΊɼϚοϓͷࣗಈߋ৽΍౔஍ར༻ௐࠪ΁ͷར༻͕‫ظ‬଴͞Ε͍ͯΔɽ౔஍ར༻ௐࠪʹԠ༻͢Δ৔߹ɼมԽͨ͠ྖҬͷ‫ݕ‬ग़͚ͩͰͳ͘ɼ೶஍΍৿ྛͳͲա‫ࡏݱͱڈ‬ͷ౔஍ͷଐੑ৘ใ͕ඞཁͰ͋Δɽ͜ΕʹΑΓɼมԽͨ͠৔ॴͷ಺༁Λ೺Ѳ͢Δ͜ͱ͕Ͱ͖Δɽͦ͜Ͱຊ‫Ͱڀݚ‬͸ɼมԽྖҬͱΦϒδΣΫτΫϥεΛಉ࣌ʹਪఆ͠ɼมԽྖҬʹ౔஍ͷଐੑ৘ใΛ෇༩͢Δ͜ͱ͕
Ͱ͖ΔมԽ఺‫ݕ‬ग़๏ΛఏҊ͢ΔɽఏҊख๏͸ɼηϚϯςΟοΫηάϝϯςʔγϣϯͱมԽ఺‫ݕ‬ग़Λ 1 ͭͷωοτϫʔΫͰ࣮‫͢ݱ‬Δɽ·ͨɼηάϝϯςʔγϣϯϞσϧΑΓநग़ͨ͠ಛ௃ϚοϓΛɼมԽ఺‫ݕ‬ग़Ϟσϧͷೖྗͱͯ͠࢖༻͢Δ͜ͱͰɼ྆λεΫͷਫ਼౓޲্ΛਤΔɽ

softmax

1. ͸͡Ίʹ

Segmentation (present)ਤ 1 : มԽ఺‫ݕ‬ग़ωοτϫʔΫͷ֓ཁ

3.3 ஈ֊తͳֶशͱଛࣦؔ਺ఏҊख๏͸ɼηάϝϯςʔγϣϯϞσϧͱมԽ఺‫ݕ‬ग़ϞσϧʹΑΓߏ੒͞Εɼஈ֊తͳֶशΛߦ͏ɽ
Step1ɿ·ͣɼϕʔεͱͳΔηάϝϯςʔγϣϯϞσϧ θsegΛֶश͢ΔɽϐΫηϧ૯਺Λ N ɼΫϥε਺Λ S, ਖ਼ղϥϕϧΛ tɼιϑτϚοΫεؔ਺ͷग़ྗΛ y ͱ͢ΔͱɼηϚϯςΟοΫηάϝϯςʔγϣϯλεΫͷଛࣦؔ਺ LSeg ͸ࣜ(1) Ͱද͢͜ͱ͕Ͱ͖Δɽ
NLSeg = −S1 !!
wc ti,c log yi,cN i c(1)͜͜Ͱɼwc ͸֤λεΫͷॏΈͰ͋ΔɽӴ੕ը૾ͳͲͷ௒ߴղ૾౓ը૾Ͱߏ੒͞ΕΔσʔληοτΛ࢖༻͢Δ৔߹ɼΫϥεෆ‫͕ߧۉ‬ੜ͡Δɽϥϕϧ͕ෆ‫ߧۉ‬ͷ··ֶश͢Δͱɼग़‫཰֬ݱ‬ͷߴ͍Ϋϥεʹରͯ͠ૣ‫ʹظ‬ऩଋͯ͠͠·͍ɼग़‫཰֬ݱ‬ͷ௿͍Ϋϥε͕΄ͱΜͲ൓ө͞Εͳ͍໰୊͕͋ΔɽͦͷͨΊɼࣜ (2) ʹࣔ͢Α͏ʹɼग़‫ ཰֬ݱ‬pc ͷ‫ʹ਺ٯ‬ର਺ΛॏΈͱ͢Δɽ
1
wc = log(2)pc͜ΕʹΑΓɼग़‫཰֬ݱ‬ͷߴ͍ΫϥεʹΦʔόʔϑΟοςΟϯά͢Δ͜ͱΛ๷͙ɽ
Step2ɿ࣍ʹɼηάϝϯςʔγϣϯϞσϧ θseg ͷॏΈΛ‫ݻ‬ఆ͠ɼมԽ఺‫ݕ‬ग़Ϟσϧ θcd Λֶश͢Δɽࣜ (2) Ͱఆٛͨ͠ॏΈΛ࢖༻͠ɼΫϥε਺Λ D ͱ͢ΔͱɼมԽ఺‫ݕ‬ग़λεΫͷଛࣦؔ਺ LDif f ͸ࣜ (3) Ͱද͢͜ͱ͕Ͱ͖Δɽ
NLDif f = −D1 !!
wc ti,c log yi,cN i c(3)Step3ɿͦͯ͠ɼ2 ͭͷϞσϧͷ૬‫܎ؔޓ‬ΛอͭͨΊɼθsegͱ θcd Λಉ࣌ʹֶश͢Δɽ૬‫܎ؔޓ‬ΛอͭͨΊͷଛࣦؔ਺LM ut Λࣜ (4) ʹࣔ͢ɽStep2 ͱಉ༷ɼLM ut ͷࢉग़ʹ͸θcd ΑΓநग़ͨ͠ಛ௃ϚοϓΛ࢖༻͢ΔɽN

LM ut = −D

1 !!
ti,c log yi,cN i c(4)Step4ɿ֤ iteration Ͱ Step1 ͔Β Step3 Λ‫܁‬Γฦ͢ɽҎ্ʹࣔ͢ஈ֊తͳֶशʹΑΓɼλεΫؒͰ৘ใΛ૬‫ޓ‬ར༻͠ɼ྆λεΫͷਫ਼౓޲্͕‫ظ‬଴Ͱ͖Δɽ

3.4 ֶशσʔλͷೖྗํ๏ఏҊख๏͸ɼ10,000×10,000 ϐΫηϧͷ௒ߴղ૾౓ը૾
Λର৅ͱ͠ɼֶश࣌͸ 512×512 ϐΫηϧʹϥϯμϜΫϩο
ϓ͢Δɽ͔͠͠ɼΫϥεෆ‫͕ߧۉ‬ੜ͡Δ৔߹ɼϥϯμϜΫϩοϓͰ͸ग़‫཰֬ݱ‬ͷ௿͍Ϋϥε͕બ୒͞Εͣɼֶश͕ෆ҆ఆͱͳΔɽͦ͜Ͱɼग़‫཰֬ݱ‬ͷ௿͍ΫϥεΛଟ͘‫ؚ‬Ήύονը૾ΛผͰ༻ҙ͠ɼ௨ৗͷύονը૾ͱͱ΋ʹֶशΛߦ͏ɽ͜ΕʹΑΓɼΫϥεෆ‫ʹߧۉ‬ΑΔӨ‫ڹ‬Λ཈͑Δ͜ͱ͕Ͱ͖ΔͨΊɼֶशͷ҆ఆੑʹͭͳ͕Δɽ

4. ධՁ࣮‫ݧ‬ఏҊख๏ͷ༗ޮੑΛࣔͨ͢ΊʹɼมԽ఺‫ݕ‬ग़‫ͼٴ‬ηϚϯςΟοΫηάϝϯςʔγϣϯͷධՁ࣮‫ݧ‬Λߦ͏ɽද 2 : มԽ఺‫ݕ‬ग़ͱηϚϯςΟοΫηάϝϯςʔγϣϯͷൺֱ݁Ռ

Semantic segmentation
Change detection
Global Accuracy Class Accuracy mean IoU Kappa Global Accuracy mean IoU Kappa
Seg
90.96
62.78
45.83
78.56
92.36
48.28
6.86
U-NetDiﬀ
99.25
54.56
17.72
CNNF-F
88.66
3.28
FC-EF-Res
89.01
71.92
98.30
25.49
Proposed
91.46
63.21
53.48
79.24
99.17
59.32
32.20

image (2006)

image (2012)

Ground Truth

Proposed

imageਤ 2 : ఏҊख๏ʹΑΔมԽ఺‫ݕ‬ग़ྫ

4.1 σʔληοτຊ࣮‫Ͱݧ‬͸ɼҟͳΔ࣌‫ࡱʹظ‬Ө͞ΕͨӴ੕ը૾ϖΞͰߏ੒͞ΕΔ HRSCD σʔληοτ [2] Λ࢖༻͢ΔɽHRSCDσʔληοτ͸ɼେ‫ن‬໛ͳ௒ߴղ૾౓ͷมԽ఺‫ݕ‬ग़༻σʔληοτͰ͋ΔɽRGB ը૾ϖΞͱɼ֤ϐΫηϧͰͷมԽ৘ใΛ෇༩ͨ͠มԽ‫ݕ‬ग़ϥϕϧ (มԽྖҬͳ͠ɼมԽྖҬ͋Γ)ɼ౔஍ར༻৘ใΛ෇༩ͨ͠ηάϝϯςʔγϣϯϥϕϧ(৘ใͳ͠ɼਓ޻෺ɼ೶‫ۀ‬஍ଳɼ৿ྛɼ࣪஍ɼਫҬ) ͕‫·ؚ‬ΕΔɽσʔλ૯਺͸ 582 ຕ͋Γɼֶश༻ʹ 292 ຕ (146 ૊ͷը૾ϖΞ)ɼධՁ༻ʹ 290 ຕ (145 ૊ͷը૾ϖΞ) Λ࢖༻͢Δɽද 1 ʹ HRSCD σʔληοτͷ֤Ϋϥεʹ͓͚Δग़‫ͱ཰֬ݱ‬ॏΈΛࣔ͢ɽද 1 ΑΓɼग़‫͕཰֬ݱ‬খ͍͞΄ͲɼΫϥεॏΈ͕େ͖͘ͳΔ͜ͱ͕Θ͔Δɽද 1 : ֤Ϋϥεʹ͓͚Δग़‫ͱ཰֬ݱ‬ॏΈSemantic Segmentation

Ground Truth

U-Net (Seg)

Proposedਤ 3 : ֤ख๏ͷηάϝϯςʔγϣϯྫ

Change Detection৘ใͳ͠ਓ޻෺

೶‫ۀ‬஍ଳ

৿ྛ

࣪஍

ਫҬ

มԽͳ͠

มԽ͋Γ

ग़‫[ ཰֬ݱ‬%]

17.70

11.51

61.84

8.36

0.02

0.58

99.23

0.77

ΫϥεॏΈ

0.0

2.16

0.48

2.48

8.54

5.15

0.01

4.87

͖ΔɽηϚϯςΟοΫηάϝϯςʔγϣϯɿද 2 ΑΓɼఏҊख๏͸શͯͷධՁࢦඪͰ࠷΋ߴਫ਼౓Ͱ͋Δ͜ͱ͕֬ೝͰ͖Δɽಛʹ U-Net (Seg) ͸ɼఏҊख๏ͷηάϝϯςʔγϣϯϞσϧͱಉҰͷωοτϫʔΫߏ଄Ͱ͋Δ͕ɼࣝผਫ਼౓͕࠷େ໿
0.7 ϙΠϯτ޲্ͨ͠ɽ͜Ε͸ɼλεΫؒͰ৘ใΛ૬‫ޓ‬ར༻͔ͨ͠ΒͰ͋Δͱߟ͑ΒΕΔɽ·ͨɼਤ 3 ΑΓ೶‫ۀ‬஍ଳͳͲͷྖҬͷ޿͍Ϋϥεͱɼ‫ݕ‬ग़͕ࠔ೉ͳ઒ͳͲྖҬ͕ࡉ͍Ϋϥεʹ͓͍ͯ΋ߴਫ਼౓ͳηάϝϯςʔγϣϯ͕Ͱ͖ͯ
͍Δ͜ͱ͕෼͔Δ.

4.4 Ϋϥεෆ‫ʹߧۉ‬ର͢Δ༗ޮੑͷௐࠪਓ޻෺ΫϥεΛ‫ؚ‬Ήύονը૾Λ௥Ճ͢Δ͜ͱʹΑΔਫ਼౓ൺֱΛߦ͏ɽද 3 ʹɼ௥Ճલͱ௥Ճ‫ͦޙ‬ΕͧΕͷఆྔతධՁΛࣔ͢ɽग़‫཰֬ݱ‬ͷ௿͍ΫϥεΛ‫ؚ‬Ήύονը૾Λ௥Ճ͢Δ͜ͱͰֶश͕҆ఆ͠ɼ΄΅શͯͷΫϥεͰਫ਼౓޲্Λ֬ೝͨ͠ɽ·ͨɼग़‫཰֬ݱ‬ͷߴ͍೶‫ۀ‬஍ଳͷ‫ࣝޡ‬ผ͕‫ݮ‬গͨ͜͠ͱͰɼ৿ྛΫϥεͷࣝผਫ਼౓͕໿ 35.7 ϙΠϯτ޲্ͨ͠ɽ
ද 3 : ೖྗํ๏มߋʹΑΔൺֱ݁Ռ

4.2 ࣮‫֓ݧ‬ཁHRSCD σʔληοτ͸ɼֶशαϯϓϧ͕গͳ͍ͨΊɼ‫ز‬Կม‫׵‬ɼϊΠζ෇Ճ౳ͷ Data Augmentation Λߦ͍ɼόϦΤʔγϣϯΛ૿Ճ͢ΔɽධՁ࣌͸ɼ௒ߴղ૾౓ը૾Λ
512×512 ϐΫηϧͷը૾ͱͯ͠λΠϧঢ়ʹ੾Γग़ͯ͠ೖྗ͢ΔɽఆྔతධՁࢦඪͱͯ͠ɼมԽ఺‫ݕ‬ग़ɼηϚϯςΟοΫηάϝϯςʔγϣϯ‫ ʹڞ‬Global Accuracyɼmean IoUɼKappa ܎਺Λ༻͍ΔɽηϚϯςΟοΫηάϝϯςʔγϣϯͰ͸ɼ͞Βʹ Class Accuracy Λ༻͍Δɽ·ͨɼఏҊख๏ͷੑೳൺֱͱͯ͠ɼU-Net ͓Αͼ CNNF-FɼFC-EF-Res Λ࢖༻͢ΔɽU-Net ͸ɼ୯ҰͷωοτϫʔΫͱͯ͠มԽ఺‫ݕ‬ग़λεΫ U-Net (Diﬀ) ͱηϚϯςΟοΫηάϝϯςʔγϣϯλεΫ U-Net (Seg) ͦΕͧΕͷֶशΛߦ͏ɽ

4.3 ֤λεΫʹ͓͚ΔධՁ݁Ռ֤ख๏Λ࢖༻ͨ࣌͠ͷɼมԽ఺‫ݕ‬ग़ͱηϚϯςΟοΫηάϝϯςʔγϣϯͷఆྔతධՁΛද 2 ʹɼఆੑతධՁΛਤ2 ͓Αͼਤ 3 ʹࣔ͢. U-Net (Seg) Ͱ͸ɼ֤ը૾ʹର͢Δηάϝϯςʔγϣϯ݁ՌΛར༻ͨ͠มԽ఺‫ݕ‬ग़Λߦ͓ͬͯΓɼը૾ؒͰΫϥε͕ҟͳΔྖҬΛมԽྖҬͱ͢ΔɽมԽ఺‫ݕ‬ग़ɿද 2 ΑΓɼఏҊख๏͕ैདྷख๏ͱൺֱ͠ɼmean
IoU ͱ Kappa ܎਺ʹ͓͍ͯߴਫ਼౓Ͱ͋Δ͜ͱ͕֬ೝͰ͖ΔɽҰํɼU-Net (Seg) Ͱ͸ηάϝϯςʔγϣϯਫ਼౓͸ߴ͍΋ͷͷɼ‫ݕ‬ग़ਫ਼౓͸௿Լͨ͠ɽ͜Ε͸ɼηάϝϯςʔγϣϯ݁Ռʹ͓͍ͯΫϥε‫ڥ‬քͷ‫ࣝޡ‬ผ͕ଟ͋͘ΔͨΊɼมԽྖҬͷ‫ݕޡ‬ग़Λট͍ͨͱߟ͑ΒΕΔɽ·ͨɼਤ 2 ΑΓఏҊख๏͸ಓ࿏ͳͲͷࡉ͍ྖҬͷ‫ݕ‬ग़ՄೳͰ͋Δ͜ͱ͕֬ೝͰ

Semantic Segmentation

Change Detectionਓ޻෺೶‫ۀ‬஍ଳ৿ྛ࣪஍

ਫҬมԽͳ͠

௥Ճલ

67.51

85.27

37.81

0.0

31.56

99.20

มԽ͋Γ17.74

௥Ճ‫ޙ‬

68.97

89.88

73.55

0.0

35.01

99.17

19.47

5. ͓ΘΓʹ
ຊ‫Ͱڀݚ‬͸ɼมԽྖҬͷΦϒδΣΫτΫϥεΛਪఆ͢Δ
͜ͱͷͰ͖ΔมԽ఺‫ݕ‬ग़๏ΛఏҊͨ͠ɽ2 ͭͷϞσϧΛ࢖
༻͢Δ͜ͱͰɼߴਫ਼౓ͳมԽྖҬͷ‫ݕ‬ग़Λ࣮‫͠ݱ‬ɼ୯Ұͷ
U-Net ಉ༷ͷηάϝϯςʔγϣϯਫ਼౓Λୡ੒ͨ͠ɽࠓ‫ޙ‬͸ɼग़‫཰֬ݱ‬ͷ௿͍ΫϥεͷߋͳΔਫ਼౓޲্Λ‫ݕ‬౼͢Δɽࢀߟจ‫ݙ‬[1] E. Amin, et al., “Convolutional neural network features
based change detection in satellite images”, First International Workshop on Pattern Recognition, 2016.
[2] R. C. Daudt, et al., “Multitask Learning for Large-scale
Semantic Change Detection”, CVIU, 2019.
[3] O. Ronneberger, et al., “U-Net: Convolutional Networks
for Biomedical Image Segmentation”, MICCAI, 2015.

‫੷ۀڀݚ‬[1] ౵Ҫॣ‫ ޗ‬౳,“ηϚϯςΟοΫηάϝϯςʔγϣϯʹΑΔ௒ߴղ૾౓ը૾͔ΒͷมԽ఺‫ݕ‬ग़”, ಈతը૾ॲཧ࣮ར༻ԽϫʔΫγϣοϓ, 2021.
(ଞ 1 ݅)