Dubawa
Tubalan Squeeze-and-Excitation (SE) suna barin cibiyar sadarwa mai jujjuyawa ta koyi nawa za ta auna nauyin kowane tasha, ta sake daidaita su bisa yanayin duniya. Wannan tsari mai arha mai kama da hankali ya lashe gasar ImageNet ta 2017 kuma ya zama daidaitaccen ginin CNN.
Cibiyoyin sadarwa na Squeeze-and-Excitation tubalin fasaha ne wanda ke shafar ingancin samfuri, farashin kayayyakin more rayuwa, latency, da aminci a sikeli.
Zurfafa nutsewa
Hu, Shen, da Sun ne suka gabatar da su a cikin 2017, toshe SE yana ƙara hankalin tashar ta musamman ga CNN. Yana aiki a matakai biyu. 'Matsi' yana amfani da matsakaita taɗi na duniya don ruguje kowane taswira (tsawo x faɗin) zuwa lamba ɗaya, yana samar da mai siffa guda ɗaya akan kowane tashoshi wanda ke taƙaita kunnawar sa a duniya. The 'excitation' yana ciyar da cewa vector ta hanyar ƙananan yadudduka masu cikakken haɗin gwiwa tare da ƙwanƙwasa (a ReLU sannan sigmoid) don samar da nauyin kowane tashar tsakanin 0 da 1. Waɗancan ma'aunin nauyi suna ninka taswirar fasalin asali na asali, haɓaka tashoshi masu amfani da damping waɗanda ba su da mahimmanci. SENet ta sami nasarar ƙalubalen rarraba ILSVRC 2017, yanke kuskuren saman-5 zuwa kusan 2.25%. Toshe yana ƙara ƙarin sigogi kaɗan kawai da ƙididdigewa, da ramummuka cikin ResNet, Inception, ko MobileNet tare da ƙaramin canji.
Fahimtar Fasaha
Matsi yana samar da vector z mai tsayin C inda z_c shine matsakaicin sarari na tashar c. Ƙaddamarwa mai ban sha'awa s = sigmoid (W2 * ReLU (W1 * z)), inda W1 ya rage girman ta hanyar raguwar rabo r (yawanci 16) kuma W2 yana mayar da shi, yana kiyaye ƙarin farashi. Fitowar ita ce taswirar shigar da sikelin taswirar tasha-hikima ta s. Wani nau'i ne na gating kai: hanyar sadarwa ta yanke shawara, daga kididdigar duniya, wace tashoshi ke da mahimmanci ga wannan takamaiman shigarwar.
Ƙwararrun Ƙwararrun hanyoyin sadarwa na Matsi-da-Farawa
Tubalan Squeeze-and-Excitation (SE) suna barin cibiyar sadarwa mai jujjuyawa ta koyi nawa za ta auna nauyin kowane tasha, ta sake daidaita su bisa yanayin duniya. Wannan tsari mai arha mai kama da hankali ya lashe gasar ImageNet ta 2017 kuma ya zama daidaitaccen ginin CNN. Cibiyoyin sadarwa na Squeeze-and-Excitation tubalin fasaha ne wanda ke shafar ingancin samfuri, farashin kayayyakin more rayuwa, latency, da aminci a sikeli. Don gina zurfin fahimta, bi da Matsala-da-Excitation Networks azaman samfurin aiki, ba fasali ɗaya ba: ayyana sakamakon da ake so, fayyace zato, da raba abin da tsarin zai iya yi da dogaro daga abin da har yanzu yana buƙatar yanke hukunci na ƙwararru.
A aikace, ƙungiyoyi masu ƙarfi da ke amfani da hanyoyin sadarwa na Squeeze-and-Excitation Networks suna haɓaka gine-gine, bayanai, da zaɓin abubuwan more rayuwa tare da dogaro da farashi. Suna rubuta ƙayyadaddun ƙa'idodin nasara, gwaji akan bayanan gaskiya da gudanawar aiki, da jujjuyawar bisa ga tsarin gazawar da aka lura maimakon cin nasara na lokaci ɗaya. Wannan shine inda fahimtar ka'idar ta juya zuwa iyawa mai dorewa a cikin samfura, manufofi, da ayyuka.
Hukunce-hukuncen gine-gine suna haifar da aiki da tsadar aiki na shekaru. A lokaci guda, Haɓaka ma'auni ɗaya na iya ɓoye manyan raunin tsarin. Hanyar da ta fi dacewa ita ce haɗa saurin gwaji tare da horon gudanarwa: gudanar da matukin jirgi, kama shaida, buga rajistan ayyukan yanke shawara, da ci gaba da sabunta abubuwan tsaro kamar yadda halayen ƙira, tsammanin mai amfani, da buƙatun tsari ke tasowa.
Dabarun Tasiri
Hukunce-hukuncen gine-gine suna haifar da aiki da tsadar aiki na shekaru.
Hukunce-hukuncen gine-gine suna haifar da aiki da tsadar aiki na shekaru. A cikin ƙawance masu inganci, ana fassara wannan zuwa ƙa'idodin aiki waɗanda za a iya aunawa, iyakokin ikon mallaka, da kuma bita-da-kullin bita don ƙungiyoyi su iya haɓaka kwarin gwiwa a maimakon ɓata shakku.
Ilimin fasaha yana taimaka wa ƙungiyoyi su zaɓi tari mai kyau, ba kawai sabon abu ba.
Ilimin fasaha yana taimaka wa ƙungiyoyi su zaɓi tari mai kyau, ba kawai sabon abu ba. A cikin ƙawance masu inganci, ana fassara wannan zuwa ƙa'idodin aiki waɗanda za a iya aunawa, iyakokin ikon mallaka, da kuma bita-da-kullin bita don ƙungiyoyi su iya haɓaka kwarin gwiwa a maimakon ɓata shakku.
Zaɓuɓɓukan injiniya mafi kyau suna rage abin dogaro a cikin samarwa.
Zaɓuɓɓukan injiniya mafi kyau suna rage abin dogaro a cikin samarwa. A cikin ƙawance masu inganci, ana fassara wannan zuwa ƙa'idodin aiki waɗanda za a iya aunawa, iyakokin ikon mallaka, da kuma bita-da-kullin bita don ƙungiyoyi su iya haɓaka kwarin gwiwa a maimakon ɓata shakku.
Aiwatar da Gaskiyar Duniya
SENet ta sami nasarar ƙalubalen rarraba na ImageNet ILSVRC 2017 ta ƙara abubuwan SE zuwa kashin baya na ResNeXt.
EfficientNet da MobileNetV3 sun haɗa samfuran SE a cikin kowane toshe don haɓaka daidaito akan na'urorin hannu
Abubuwan gano abubuwa da ƙirar rarrabuwa suna saka shingen SE don jaddada tashoshi fasalin fasali
ECA-Net da CBAM suna ƙaddamar da ra'ayin SE tare da sake fasalin tashar mai rahusa ko sane
Hanyoyin Aiwatarwa
Matsi-da-Excitation Networks a aikace
SENet ta sami nasarar ƙalubalen rarraba ImageNet ILSVRC 2017 ta ƙara abubuwan SE zuwa ga kashin baya na ResNeXt.
SENet ta lashe ƙalubalen rarraba na ImageNet ILSVRC 2017 ta ƙara SE blocks zuwa ResNeXt Ƙungiyoyin kashin baya yawanci suna samun sakamako mafi kyau lokacin da suka ayyana ma'auni masu inganci a gaba, kiyaye hanyar haɓakar ɗan adam don ƙararrakin ƙira, da kuma bin diddigin abubuwan da ake samu da ƙimar kuɗi a kan lokaci.
Matsi-da-Excitation Networks a aikace
EfficientNet da MobileNetV3 sun haɗa samfuran SE a cikin kowane toshe don haɓaka daidaito akan na'urorin hannu.
EfficientNet da MobileNetV3 sun haɗa nau'ikan SE a cikin kowane toshe don haɓaka daidaito akan na'urorin hannu Ƙungiyoyi yawanci suna samun sakamako mafi kyau lokacin da suka ayyana ma'auni masu inganci a gaba, kiyaye hanyar haɓakar ɗan adam don shari'o'i, da bin duk nasarorin samarwa da ƙimar kuskure akan lokaci.
Matsi-da-Excitation Networks a aikace
Abubuwan gano abubuwa da ƙirar rarrabuwa suna saka shingen SE don jaddada tashoshi fasalin fasali.
Masu gano abubuwa da samfuran rarrabuwa suna saka shingen SE don jaddada tashoshi na fasali masu ba da labari Ƙungiyoyi yawanci suna samun sakamako mafi kyau lokacin da suka ayyana ƙofofin inganci a gaba, kiyaye hanyar haɓakar ɗan adam don shari'o'in gefe, da bin duk nasarorin samarwa da ƙimar kuskure akan lokaci.
Matsi-da-Excitation Networks a aikace
ECA-Net da CBAM suna ƙaddamar da ra'ayin SE tare da sake fasalin tashar mai rahusa ko sane.
ECA-Net da CBAM suna ƙaddamar da ra'ayin SE tare da rahusa ko kuma sane da ƙungiyoyin sake gyara tashar tashoshi yawanci suna samun sakamako mafi kyau lokacin da suka ayyana ma'auni masu inganci a gaba, kiyaye hanyar haɓakar ɗan adam don ƙararraki, da bin diddigin nasarorin samarwa da farashi na kuskure akan lokaci.
Hatsari & Tsare-tsare
Haɓaka ma'auni ɗaya na iya ɓoye manyan raunin tsarin.
Sau da yawa ana raina kayan more rayuwa da kuma kuɗin kulawa.
Tsaro da gibin lura na iya girma yayin da tsarin ke ƙara haɓaka.
Taswirar Hanya
Ƙayyade latency, inganci, da maƙasudin farashi kafin aiwatarwa.
Ƙayyade latency, inganci, da maƙasudin farashi kafin aiwatarwa. Ɗauki kowane mataki azaman ƙofar shaida: idan ba a cika sharuɗɗa ba, dakatar da fitar, rufe tazarar, sannan kawai faɗaɗa amfani.
Alamar ma'auni a ƙarƙashin ainihin kaya da yanayin bayanai.
Alamar ma'auni a ƙarƙashin ainihin kaya da yanayin bayanai. Ɗauki kowane mataki azaman ƙofar shaida: idan ba a cika sharuɗɗa ba, dakatar da fitar, rufe tazarar, sannan kawai faɗaɗa amfani.
Kula da kayan aiki don kurakurai, ɗigo, da tasirin mai amfani.
Kula da kayan aiki don kurakurai, ɗigo, da tasirin mai amfani. Ɗauki kowane mataki azaman ƙofar shaida: idan ba a cika sharuɗɗa ba, dakatar da fitar, rufe tazarar, sannan kawai faɗaɗa amfani.
Shirya bijirowa da hanyoyin mayar da martani kafin sikeli.
Shirya bijirowa da hanyoyin mayar da martani kafin sikeli. Ɗauki kowane mataki azaman ƙofar shaida: idan ba a cika sharuɗɗa ba, dakatar da fitar, rufe tazarar, sannan kawai faɗaɗa amfani.