Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Features
Speaker Deck
PRO
Sign in
Sign up for free
Search
Search
Shoe Recognition Model with Floor Pressure Sens...
Search
yumulab
November 06, 2024
Research
0
42
Shoe Recognition Model with Floor Pressure Sensors (Slide)
2024年11月3日(日)〜7日(木)に開催されたSENSORCOMM2024の発表資料(スライド)
yumulab
November 06, 2024
Tweet
Share
More Decks by yumulab
See All by yumulab
研究室から社会へ 〜 情報科学でつなぐ科学技術コミュニケーション実践 / #CoSTEP20th
yumulab
0
54
A Proposal of an Information Delivery Method using Human Movement as a Communication Medium for Electronic Paper Signage / ICEC2025
yumulab
0
13
メタバース空間で対話相⼿に向かって⾃律移動するAIアバター『ノア』の開発 / EC2025-Oyamada
yumulab
0
25
足位置の視覚的提示による電子オルガンのペダル鍵盤演奏学習支援システムの提案 / EC2025-Hokin
yumulab
0
23
電子ペーパーサイネージにおける人の移動を通信媒介とした情報配送手法の提案 / EC2025-Akiba
yumulab
0
17
フィジカルコンピューティングでアイデアをカタチに! / hiu-physcom
yumulab
0
39
大学内にファブスペースをつくってみた #sapporo3dp / Making HIU Fab
yumulab
1
71
感圧導電シートを用いた床面圧力センサによる人物同定手法の開発 / HCI213
yumulab
0
15
ASSADS:ASMR動画に合わせて撫でられる感覚を提示するシステムの開発と評価 / ec75-shimizu
yumulab
1
620
Other Decks in Research
See All in Research
Google Agent Development Kit (ADK) 入門 🚀
mickey_kubo
2
2.2k
20250605_新交通システム推進議連_熊本都市圏「車1割削減、渋滞半減、公共交通2倍」から考える地方都市交通政策
trafficbrain
0
910
EarthDial: Turning Multi-sensory Earth Observations to Interactive Dialogues
satai
3
260
財務諸表監査のための逐次検定
masakat0
0
150
Panopticon: Advancing Any-Sensor Foundation Models for Earth Observation
satai
3
250
世界の人気アプリ100個を分析して見えたペイウォール設計の心得
akihiro_kokubo
PRO
63
32k
「どう育てるか」より「どう働きたいか」〜スクラムマスターの最初の一歩〜
hirakawa51
0
960
PhD Defense 2025: Visual Understanding of Human Hands in Interactions
tkhkaeio
1
270
長期・短期メモリを活用したエージェントの個別最適化
isidaitc
0
210
Sat2City:3D City Generation from A Single Satellite Image with Cascaded Latent Diffusion
satai
3
160
MetaEarth: A Generative Foundation Model for Global-Scale Remote Sensing Image Generation
satai
4
350
能動適応的実験計画
masakat0
2
880
Featured
See All Featured
Design and Strategy: How to Deal with People Who Don’t "Get" Design
morganepeng
132
19k
The Power of CSS Pseudo Elements
geoffreycrofte
80
6k
Writing Fast Ruby
sferik
630
62k
The Straight Up "How To Draw Better" Workshop
denniskardys
238
140k
Six Lessons from altMBA
skipperchong
29
4k
Become a Pro
speakerdeck
PRO
29
5.6k
Typedesign – Prime Four
hannesfritz
42
2.8k
CoffeeScript is Beautiful & I Never Want to Write Plain JavaScript Again
sstephenson
162
15k
VelocityConf: Rendering Performance Case Studies
addyosmani
333
24k
Documentation Writing (for coders)
carmenintech
75
5.1k
RailsConf 2023
tenderlove
30
1.3k
Leading Effective Engineering Teams in the AI Era
addyosmani
7
640
Transcript
Shoe Recognition Model with Floor Pressure Sensors Sora Kamimura *1
Tetsuo Yutani *2 Atsuko Shibuya *2 Tsubasa Yumura *1 *1 Hokkaido Information University *2 FirstFourNotes, LLC <%FNP>
Table of contents #BDLHSPVOE1VSQPTF 1SFTTVSFTFOTPS .PEFM
%BUBTFUT 3FTVMU%JTDVTTJPO $PODMVTJPO
#BDLHSPVOE1VSQPTF 5SB ffi D fl PXBOBMZTJT #ZDBNFSB 4VSWFJMMBODFDBNFSBTDBOCFEJWFSUFE $BONBOBHFBMBSHFBSFBCZPOFDBNFSB *OWBTJPOPGQSJWBDZ
#MJOETQPUTDBVTFECZPCTUBDMFT ɾ*NQSPWFEXPSLF ffi DJFODZ ɾ"WPJESJTL DPMMJTJPOT GBMMT FUDʜ #Z fl PPSQSFTTVSFTFOTPS /PQSJWBDZJTTVF /PCMJOETQPUT
#BDLHSPVOE1VSQPTF 5SB ff i D fl PXBOBMZTJTCBTFE fl PPSQSFTTVSFTFOTPS SFRVJSFTJEFOUJ
fi DBUJPOPGQFPQMF )VNBOJEFOUJ fi DBUJPOVTFT XFJHIU TUSJEFMFOHUI TQFFE TIPFUZQF FUD *OUIJTTUVEZ XFEFWFMPQUIF TIPFSFDPHOJUJPONPEFMXJUI fl PPSQSFTTVSFTFOTPST
1SFTTVSFTFOTPS .BUFSJBMT ɾ7FMPTUBU QSFTTVSFTFOTJUJWFDPOEVDUJWFTIFFU ɾ$PQQFSGPJMUBQF ɾ"SEVJOP 4USVDUVSF ɾ$PQQFSGPJMUBQFTBSFNNXJEFBOE ɹTQBDFENNBQBSU ɾUBQFTCPUIWFSUJDBMMZBOEIPSJ[POUBMMZ
ɾNFBTVSFNFOUQPJOUT ɾ.FBTVSFUIFWPMUBHFBUFBDIQPJOUFWFSZNT
.PEFM ɾ5IF*OQVUMBZFSSFDFJWFTSBXEBUB ɾ5IFIJEEFOMBZFSJTUISFFGVMMZDPOOFDUFEMBZFS ɾ5IFPVUQVUMBZFSXJMMPVUQVUUIFTIPFJEFOUJ fi DBUJPOFTUBCMJTINFOU ɹ TOFBLFS SPPNTIPF BOETBOEBM
/FVSBMOFUXPSLNPEFM
%BUBTFUT )PXUPDPMMFDU $BMJCSBUJPOUIFTFOTPS 1VUPOTIPF 8BJUBGFXTFDPOET TPST
.FBTVSFNFOUT .FBTVSFNFOUTUJNFT JOFBDITIPF %BUB5ZQF ɾ&BDITFOTPS ʙ PS.FSHFE ɾ)PXMPOHXBJUGPSNFBTVSF TPST ɾ/PSNBMPS3PUBUFEEFHSFFTGPS ɹEBUBBVHNFOUBUJPO
3FTVMU ɾ5IF'NFBTVSFJOTJT ɹIJHIFSUIBOT ˠ7JCSBUJPOTBOEPUIFSOPJTFTJT ɹMFTTCZXBJUJOH ɾ*OTFDPOET UIF'NFBTVSFPG ɹNFSHFEEBUBJTIJHIFSUIBO ɹFBDITFOTPSEBUB ˠ5IFTFOTPSIBTBTFOTJUJWJUZCJBT
ɹ"OE NPEFMDBOUMFBSOJUCZ ɹFBDITFOTPSEBUB ɹ#VUMFBSOJOHCFDBNFQPTTJCMFCZ ɹNFSHFEEBUB 'NFBTVSF F = 2 × precision × recall precision + recall
$PODMVTJPO ɾ*OUIJTTUVEZ XFEFWFMPQFEUIFOFVSBMOFUXPSLNPEFMUPSFDPHOJ[F ɹTIPFUZQFTXJUI fl PPSQSFTTVSFTFOTPSXJUIB7FMPTUBU ɾ6TJOHBSPUBUFEEBUBTFUQSPWFEUPCFUIFNPTUF ff FDUJWFBQQSPBDIGPS ɹSFBMXPSMEBQQMJDBUJPOT
ɾ5IFSFBSFMBSHFEJ ff FSFODFCFUXFFOUIFFYQFSJNFOUBMFOWJSPONFOU ɹBOEUIFBTTVNFESFBMFOWJSPONFOU ɾ5IFSFBSFQSPCMFNTTVDIBTSFBDUJPOSBUFBOEBMMPXBCMFQSFTTVSF ɾ8FXJMMDPOUJOVFUPEFWFMPQCPUIIBSEXBSFBOETPGUXBSFUPTPMWF ɹUIFTFQSPCMFNT