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As a result, to achieve the robust performance, initially the joint trilateral and bilateral filter (JTBF) with convolutional auto encoder and decoder (CAED)-based preprocessing method is used to enhance the skin lesion and also removes hair from lesions. Then, transfer learning-based probabilistic multi-layer dense networks (PMDN) method-based unmanned Transfer learning segmentation method is adapted for accurately detecting the cancer region on skin lesions. Further, transfer learning convolution neural network (TL-CNN) is used to extract the features from the segmented region, which extracts the detailed inter-disease-dependent (IDD) and intra-disease specific (IDS) features. Finally, Alexa Net model is trained and tested with the IDD, IDS features and classifies the eight different skin cancer types. The complexity of the transfer learning networks is optimized by the using the Adam optimizer. Finally, the simulation results show that the proposed model resulted in superior segmentation, feature extraction, and classification performances as compared to conventional approaches. Further, the proposed method achieved 99.937% segmentation accuracy, 99.47% feature extraction accuracy, and 99.27% classification accuracy on ISIC-2019 public challenge dataset. <\/jats:p>","DOI":"10.1142\/s1469026822500274","type":"journal-article","created":{"date-parts":[[2022,12,26]],"date-time":"2022-12-26T07:27:41Z","timestamp":1672039661000},"source":"Crossref","is-referenced-by-count":10,"title":["Detection and Classification of Skin Cancer Using Unmanned Transfer Learning Based Probabilistic Multi-Layer Dense Networks"],"prefix":"10.1142","volume":"21","author":[{"given":"V.","family":"Nyemeesha","sequence":"first","affiliation":[{"name":"Department of Computer Science Engineering, Koneru Lakshmaiah Education Foundation Greenfields, Vaddeswaram, Guntur 522502, Andhra Pradesh, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"M.","family":"Kavitha","sequence":"additional","affiliation":[{"name":"Department of Computer Science Engineering, Koneru Lakshmaiah Education Foundation Greenfields, Vaddeswaram, Guntur 522502, Andhra Pradesh, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"B.","family":"Mohammed Ismail","sequence":"additional","affiliation":[{"name":"Department of Computer Science Engineering, Koneru Lakshmaiah Education Foundation Greenfields, Vaddeswaram, Guntur 522502, Andhra Pradesh, India"},{"name":"Department of Artificial Intelligence & Machine Learning, P.A. 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