A Speed-Up Scheme Based on Multiple-Instance Pruning for Pedestrian Detection Using a Support Vector Machine Abstract?A Speed-Up Scheme Based on Multiple-Instance Pruning for Pedestrian Detection Using a Support Vector Machine. In pedestrian detection, as sophisticated feature descriptors are used for improving detection accuracy, its processing speed becomes a critical issue. In this paper, we propose…
A Statistical Modeling Approach for Tumor-Type Identification in Surgical Neuropathology Using Tissue Mass Spectrometry Imaging Abstract?Current clinical practice involves classification of biopsied or resected tumor tissue based on a histopathological evaluation by a neuropathologist. In this paper, we propose a method for computer-aided histopathological evaluation using mass spectrometry imaging. Specifically, mass spectrometry imaging can…
A Strategy of Clustering Modification Directions in Spatial Image Steganography Abstract? Most of the recently proposed steganographic schemes are based on minimizing an additive distortion function de?ned as the sum of embedding costs for individual pixels. In such an approach, mutual embedding impacts are often ignored. In this paper, we present an approach that can…
A Suitable Initialization Procedure for Speeding a Neural Network Job-Shop Scheduling Abstract? Artificial neural network models have been successfully applied to solve a job-shop scheduling problem (JSSP) known as a Nonpolynomial (NP-complete) constraint satisfaction problem. Our main contribution is an improvement of the algorithm proposed in the literature. It consists in using a procedure…
A Survey on Diseases Detection and Classification of Cotton Leaf Abstract-At the first place, agriculture is one of the demanded field of the country like India and also number of research is going on in agriculture among that found still limitation. Identification of plant disease is very difficult in agriculture field. If identification is incorrect…
A Three-Layered Graph-Based Learning Approach for Remote Sensing Image Retrieval Abstract?With the emergence of huge volumes of high-resolution remote sensing images produced by all sorts of satellites and airborne sensors, processing and analysis of these images require effective retrieval techniques. < final year projects > [numbers_sections number=”1″ title=”Including =Packages=” last=”no” ] Complete Source Code Complete…
A Visual Model-Based Perceptual Image Hash for Content Authentication Abstract?Perceptual image hash has been widely investigated in an attempt to solve the problems of image content authentication and content-based image retrieval. In this paper, we combine statistical analysis methods and visual perception theory to develop a real perceptual image hash method for content authentication. To…
Abandoned Object Detection via Temporal Consistency Modeling and Back-Tracing Verification for Visual Surveillance Abstract? An effective approach for detecting < Final Year Projects 2016 > abandoned luggage in surveillance videos. We combine short- and long-term background models to extract foreground objects, where each pixel in an input image is classi?ed as a 2-bit code. Subsequently,…
Abnormal crowd behaviour detection by using partical entorpy Abstract? Abnormal crowd behaviour detection by using partical entorpy. We propose a fully unsupervised method for abnormal activity detection in crowded scenes. Neither normal nor abnormal training examples are needed before detection. By observing that in crowded scenes, normal activities are the behaviors performed by the majority…
Action Recognition in Still Images With Minimum Annotation Efforts Abstract? The problem of still image-based human action recognition, which essentially involves making prediction by analyzing human poses and their interaction with objects in the scene. Besides image-level action labels (e.g., riding, phoning), during both training and testing stages, existing works usually require additional input of…
Adaptive Image Denoising by Targeted Databases Abstract? Adaptive Image Denoising by Targeted Databases. A data-dependent denoising procedure to restore noisy images. Different from existing denoising algorithms which search for patches from either the noisy image or a generic database, the new algorithm ?nds patches from a database that contains relevant patches. We formulate the denoising…
Adherent Raindrop Modeling, Detection and Removal in Video Abstract? Raindrops adhered to a windscreen or window glass can significantly degrade the visibility of a scene. Modeling, detecting and removing raindrops will, therefore, benefit many computer vision applications, particularly outdoor surveillance systems and intelligent vehicle systems. In this paper, a method that automatically detects and removes…
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