This research study analyzes the multidimensional landscape of steganography, examining its historical roots, theoretical background, contemporary approaches, and various applications. Beginning with a historical over...
详细信息
ISBN:
(纸本)9798350391558;9798350379990
This research study analyzes the multidimensional landscape of steganography, examining its historical roots, theoretical background, contemporary approaches, and various applications. Beginning with a historical overview, this study investigates the evolution of steganography from its ancient roots to its present iterations in the digital world. Next, the study progresses towards analyzing the fundamental principles and theoretical frameworks that underpin steganographic systems, such as cryptography and digital signal processing. Finally, this study presents a thorough evaluation of contemporary steganographic technologies, which range from simple LSB (Least Significant Bit) substitution techniques to advanced adaptive algorithms and machine learning methods by including deep-learning based steganography and coverless steganography. Notably, this study identifies key challenges, including detection resistance, payload capacity, and robustness against attacks. Overall, this study presents a thorough understanding of steganography, emphasizing its significance as a versatile tool for communication in the digital era, while also highlighting the challenges that pave way for future innovations.
Recently, machine learning algorithms have been widely used in the fields of imageprocessing, network security and natural language processing, etc., profoundly affecting human life. However, machine learning algorit...
详细信息
The strong temporal consistency of surveillance video enables compelling compression performance with traditional methods, but downstream vision applications operate on decoded image frames with a high data rate. Sinc...
详细信息
ISBN:
(纸本)9798400704123
The strong temporal consistency of surveillance video enables compelling compression performance with traditional methods, but downstream vision applications operate on decoded image frames with a high data rate. Since it is not straightforward for applications to extract information on temporal redundancy from the compressed video representations, we propose a novel system which conveys temporal redundancy within a sparse decompressed representation. We leverage a video representation framework called AD Delta ER to transcode framed videos to sparse, asynchronous intensity samples. We introduce mechanisms for content adaptation, lossy compression, and asynchronous forms of classical vision algorithms. We evaluate our system on the VIRAT surveillance video dataset, and we show a median 43.7% speed improvement in FAST feature detection compared to OpenCV. We run the same algorithm as OpenCV, but only process pixels that receive new asynchronous events, rather than process every pixel in an image frame. Our work paves the way for upcoming neuromorphic sensors and is amenable to future applications with spiking neural networks.
Absorption, scattering, and colour distortion make underwater photography difficult. Marine biology, underwater archaeology, and surveillance need better underwater photos. This research compares cutting-edge underwat...
详细信息
The proceedings contain 23 papers. The topics discussed include: solar powered auto irrigation monitoring system with plant health indication using imageprocessing;large language model and artificial intelligence bas...
ISBN:
(纸本)9798331508692
The proceedings contain 23 papers. The topics discussed include: solar powered auto irrigation monitoring system with plant health indication using imageprocessing;large language model and artificial intelligence based human conversation agent;to enhance graph-based retrieval-augmented generation (RAG) with robust retrieval techniques;automatic timetable generation using neural networks trained by genetic algorithms;assessment of efficient and cost-effective vehicle detection in foggy weather;enhanced detection and prevention of SQL injection and cross-site scripting attacks in web applications: analyzing algorithms and threat modeling approaches;efficient duplicate question detection;and a comprehensive survey on computing services to detect stress and anxiety using smart devices.
Vehicle positioning algorithms are essential for improving traffic management and safety by accurately locating vehicles in real-time, and, thus, minimizing congestion and accidents. They also support the development ...
详细信息
ISBN:
(纸本)9798350364309;9798350364293
Vehicle positioning algorithms are essential for improving traffic management and safety by accurately locating vehicles in real-time, and, thus, minimizing congestion and accidents. They also support the development of advanced driver assistance systems and autonomous vehicles, relying on precise positioning data for safe navigation. One of the solutions involves using imageprocessingalgorithms, which can have two approaches. One approach is decentralized, in which each vehicle performs its own computing steps and determines its position concerning the other nearby vehicles. The second approach, proposed in this paper, is centralized, where each vehicle sends data to a server that uses cloud computing to process all the data in real-time. As such, vehicles can create a more comprehensive view of the driving conditions in the area by using either of these two approaches, which can help them anticipate potential hazards and make more informed decisions.
In the context of healthcare and human-computer interaction., this research study provides a thorough analysis of sophisticated computational algorithms for data classification, picture processing, and disease predict...
详细信息
To concurrently address the challenges of automatic modulation recognition (AMR) and modulation parameter estimation (MPE) in radar signals, we introduce a multi-task learning (MTL) network architecture designed for i...
详细信息
ISBN:
(纸本)9798350351040;9798350351033
To concurrently address the challenges of automatic modulation recognition (AMR) and modulation parameter estimation (MPE) in radar signals, we introduce a multi-task learning (MTL) network architecture designed for intra-pulse multi-parameter recognition through automatic noise reduction. The proposed approach initiates by generating time -frequency image (rn) directly from noisy time-domain signal using a neural network. To effectively capture relevant features from TFls, we employ a VGG-like network Subsequently, the multitask learning framework is utilized to achieve AMR and MPE simultaneously. Four typical intra-pulse modulated signals were simulated in the experiments, simulation results verify the effectiveness and reliability of the proposed algorithms.
The paper presents a description of the developed algorithm for changing the size of a multi-element aperture of a recursive-separable five-stage filter for processing digital images generated by specialized optical s...
详细信息
The indoor imaging visible light positioning (VLP) technology based on the image sensor (IS) utilizes existing indoor lighting infrastructure to provide high-precision indoor positioning services. However, due to the ...
详细信息
暂无评论