Accurate segmentation of skin lesions is still a challenging task for automatic diagnostic systems because the significant shape variations and blurred boundaries lesions. This paper proposes multi-scale convolutional neural network, REDAUNet, based on UNet3+ to enhance network performance practical applications in segmentation. First, employs new encoder module composed four feature extraction...

Abstract: Purpose: This study aims to analyse technical efficiency of large and medium manufacturing industries (LMMIs) in West Java Province, Indonesia. Method: The slacks-based measure (SBM) data envelopment analysis (DEA) is used accomplish the objective study. output measured by total value thousand rupiahs; while inputs are: labour cost, cost materials, fuels, electricity, fixed capital co...

This paper studies the end-to-end uplink (UL) and downlink (DL)-outage probability (OP) of an Internet Things (IoT) network with radio frequency (RF) energy harvesting (EH) over Nakagami-m fading channels. Power-domain nonorthogonal multiple access (NOMA) is adopted to support both UL DL transmissions increase spectral efficiency. The system outage probabilities are analyzed where exact closed-...

__________________________________________________________________ This paper develops a methodology for predicting the impact of trade liberalization on exports by industry (3-digit ISIC) based on the pre-liberalization distribution of exports by product (5-digit SITC). Using the results of Kehoe and Ruhl (2013) that much of the growth in trade after trade liberalization is in products that ar...

<span>Skin cancer is one of the most dangerous types cancer. Some this lead to death, so must be discovered and indexed avoid its spread through initial detection in impulsive stage. This paper deals with indexing different melanomas using an artificial neural network (ANN) depending on international skin imaging collaboration (ISIC) 2018 dataset that was used. The pre-processing importan...

Skin cancer is a serious health hazard for human society. This disease developed when the pigments that produce skin color become cancerous. Dermatologists face difficulties in diagnosing since many colors seem identical. As result, early diagnosis of lesions (the foundation cancer) very crucial and beneficial totally curing patients. Significant progress has been made creating automated method...

Training of neural networks for automated diagnosis of pigmented skin lesions is hampered by the small size and lack of diversity of available datasets of dermatoscopic images. We tackle this problem by releasing the HAM10000 (“Human Against Machine with 10000 training images”) dataset. We collected dermatoscopic images from different populations acquired and stored by different modalities. Giv...

As one kind of skin cancer, melanoma is very dangerous. Dermoscopy based early detection and recognization strategy is critical for melanoma therapy. However, well-trained dermatologists dominant the diagnostic accuracy. In order to solve this problem, many effort focus on developing automatic image analysis systems. Here we report a novel strategy based on deep learning technique, and achieve ...

With the increasing incidence of severe skin diseases, such as cancer, endoscopic medical imaging has become urgent for revealing internal and hidden tissues under skin. Diagnostic information to help doctors make an accurate diagnosis is provided by endoscopy devices. Nonetheless, most diseases have similar features, which it challenging dermatologists diagnose patients accurately. Therefore, ...