Abstract Evaluation and benchmarking of real-time skin detectors remain challenging
because of multiple evaluation attributes that must be considered. Numerous evaluation and …

Real-time detection of humans is an evolutionary research topic. It is an essential and
prominent component of various vision based applications. Detection of humans in real-time …

Abstract Machine learning techniques are being increasingly used for detection and
diagnosis of diseases for its accuracy and efficiency in pattern classification. In this paper …

Skin detection from images, typically used as a preprocessing step, has a wide range of
applications such as dermatology diagnostics, human computer interaction designs, and etc …

This study aimed to develop a new methodology for evaluating and benchmarking a multi-
agent learning neural network and Bayesian model for real-time skin detectors based on …

We propose a two‐stage convolutional neural network (CNN) architecture for robust
recognition of hand gestures, called HGR‐Net, where the first stage performs accurate …

Color is an efficient feature for object detection as it has the advantage of being invariant to
changes in scaling, rotation, and partial occlusion. Skin color detection is an essential …

In this paper, we introduce a new self-adaptive algorithm for segmenting human skin regions
in color images. Skin detection and segmentation is an active research topic, and many …

Evaluation and benchmarking of skin detectors are challenging tasks because of multiple
evaluation attributes and conflicting criteria. Although several evaluating and benchmarking …

We designed an interface to support hand rehabilitation tasks to restore hand function and
relieve discomfort. The interface requires accurate hand segmentation, which is impeded by …