… In this paper, we proposed a gastrointestinal endoscopic image classification method
based on the combination of midlevel CNN features and the capsule network. Extensive …

… image-based diagnosis using convolutional neural networks (CNNs), which already exceed
humans in general image recognition. … cancer histology, skin cancer, and gastric cancer. …

… Network (DNN) with DH-DSU-based hidden neuron optimisation. This provides the classification
outcome in terms of three diseases of the GI … for the WCE bleedy image classification. It …

… Recently, wireless capsule endoscopy (WCE) technology has … WCE wirelessly captures
colour images of GIT in an average … in image processing to improve the contrast of given image. …

… of using convolutional neural networks in various areas of capsule endoscopy. The … AI in
technological evolution in the area of digestive endoscopy, the overwhelming majority of studies …

… image processing operations on the original 900 test images, corresponding to three test
cases, as shown in Figure 3. The validity of the proposed network … WCE gastrointestinal image …

… This study adopts a deep neural network approach and proposes a model name BIR (… Wan,
“Identification of lesion images from gastrointestinal endoscope based on feature extraction …

… (pre-trained in natural image processing tasks) for medical image analysis. Encouraged by
… , in medical image analysis, we proposed to learn robust intestinal hemorrhage detection …

… disease detection, which is able to view the entire gastrointestinal tract without pain. Since
… a network φ which has been pretrained for image classification as a fixed loss network to …

… In addition, we define a discriminator network D to … images where the esophagus meets
the stomach) and for pylorus … image processing applications, ranging from image analysis to …