State-of-the-art methods for X-ray image classification. Summarised in terms of the classifier, preprocessing, and features extraction used and their performance using the differen... by Antonio Quintero-Rincón (21087716)

Detection and Analysis of Nodule in Mammographic images using false positive reduction Detection Technique by Dr.E.N. Ganesh (12315038)

“…The second</p> <p>approach is based on an extension of his PCA approach using the recently proposed 2DPCA</p> <p>algorithm. Finally, a third approach is based on local binary patterns (LBPs) to represent texture</p> <p>information while preserving the spatial structure of the mass. …”

Hair removal preprocessing using the DullRazor algorithm before image generation. by Mujung Kim (22367223)

“…<p>The DullRazor algorithm systematically removes hair artifacts through a multi-step process: (1) converting the original hairy input image to grayscale, (2) applying a black hat filter to detect and isolate hair structures, (3) creating a binary mask of detected hair regions, and (4) removing hair regions and inpainting the underlying skin texture. …”

Table_1_Fusion of fruit image processing and deep learning: a study on identification of citrus ripeness based on R-LBP algorithm and YOLO-CIT model.docx by Chenglin Wang (430151)

“…The experiment showed that the R-LBP algorithm is capable of amplifying the texture features among citrus fruits at distinct ripeness stages. …”

Image3_DFUCare: deep learning platform for diabetic foot ulcer detection, analysis, and monitoring.jpeg by Varun Sendilraj (19732510)

“…</p>Methods<p>We developed DFUCare, a platform that leverages computer vision and deep learning (DL) algorithms to localize, classify, and analyze DFUs non-invasively. …”

Image4_DFUCare: deep learning platform for diabetic foot ulcer detection, analysis, and monitoring.jpeg by Varun Sendilraj (19732510)

“…</p>Methods<p>We developed DFUCare, a platform that leverages computer vision and deep learning (DL) algorithms to localize, classify, and analyze DFUs non-invasively. …”

Image1_DFUCare: deep learning platform for diabetic foot ulcer detection, analysis, and monitoring.jpeg by Varun Sendilraj (19732510)

“…</p>Methods<p>We developed DFUCare, a platform that leverages computer vision and deep learning (DL) algorithms to localize, classify, and analyze DFUs non-invasively. …”

Image2_DFUCare: deep learning platform for diabetic foot ulcer detection, analysis, and monitoring.jpeg by Varun Sendilraj (19732510)

“…</p>Methods<p>We developed DFUCare, a platform that leverages computer vision and deep learning (DL) algorithms to localize, classify, and analyze DFUs non-invasively. …”

Image5_DFUCare: deep learning platform for diabetic foot ulcer detection, analysis, and monitoring.jpeg by Varun Sendilraj (19732510)

“…</p>Methods<p>We developed DFUCare, a platform that leverages computer vision and deep learning (DL) algorithms to localize, classify, and analyze DFUs non-invasively. …”

Table1_DFUCare: deep learning platform for diabetic foot ulcer detection, analysis, and monitoring.docx by Varun Sendilraj (19732510)

“…</p>Methods<p>We developed DFUCare, a platform that leverages computer vision and deep learning (DL) algorithms to localize, classify, and analyze DFUs non-invasively. …”

Thesis-RAMIS-Figs_Slides by Felipe Santibañez-Leal (10967991)

“…In the context of facies recovery using simulations, the task of optimal sampling is formalized and addressed using a maximum information extraction criterion. …”