Results 31 to 40 of about 148,419 (252)
Efficient Coding of the Embedded Signal in Steganographic Systems with Multiple Access [PDF]
Problems of the Regional Energetics, 2021 Today, steganographic systems with multiple access are of considerable importance. In such sys-tems, the orthogonal Walsh-Hadamard transform is most often used for multiplexing and divid-ing channels, which leads to the need for efficient coding of the ...
Kobozeva A.A., Kobozeva A.A.,
doaj +1 more source
Block Walsh–Hadamard Transform-based Binary Layers in Deep Neural Networks [PDF]
ACM Transactions on Embedded Computing Systems, 2022 Convolution has been the core operation of modern deep neural networks. It is well known that convolutions can be implemented in the Fourier Transform domain.
Hongyi Pan, Diaa Badawi, A. Cetin
semanticscholar +1 more source
Comparison of Image Compressions: Analog Transformations
Proceedings, 2020 A comparison between the four most used transforms, the discrete Fourier transform (DFT), discrete cosine transform (DCT), the Walsh–Hadamard transform (WHT) and the Haar-wavelet transform (DWT), for the transmission of analog images, varying their ...
Jose Balsa
doaj +1 more source
Deep Neural Network with Walsh-Hadamard Transform Layer For Ember Detection during a Wildfire
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2022 In this article, we describe an ember detection method in infrared (IR) video. Embers, also called firebrands, can act as wildfire super-spreaders. We develop a novel neural network with a Walsh-Hadamard Transform (WHT) layer to process the IR video. The
Hongyi Pan +5 more
semanticscholar +1 more source
Robust Steganographic Method with Code-Controlled Information Embedding [PDF]
Problems of the Regional Energetics, 2021 In view of the fact that most images are compressed when transmitted through telecommunica-tion systems and telecommunication systems in the energetics, from the point of view of the practical use of steganographic algorithms in real information security
Kobozeva A.A. , Sokolov A.V
doaj +1 more source
Towards Lightweight Transformer via Group-wise Transformation for Vision-and-Language Tasks [PDF]
, 2022 Despite the exciting performance, Transformer is criticized for its excessive parameters and computation cost. However, compressing Transformer remains as an open problem due to its internal complexity of the layer designs, i.e., Multi-Head Attention (MHA) and Feed-Forward Network (FFN).
arxiv +1 more source
Electronics Letters, Volume 59, Issue 22, November 2023., 2023 The letter proposes a novel approach based on the adaptive selection of an ensemble of transforms to enhance the identification performance of Radio Frequency Fingerprinting in comparison to methods commonly applied in literature. The proposed approach is evaluated on a public data set in different Signal to Noise Ratio (SNR) conditions. Abstract Radio
Gianmarco Baldini
wiley +1 more source
Walsh–Hadamard Kernel Feature-Based Image Compression Using DCT with Bi-Level Quantization
Computers, 2022 To meet the high bit rate requirements in many multimedia applications, a lossy image compression algorithm based on Walsh–Hadamard kernel-based feature extraction, discrete cosine transform (DCT), and bi-level quantization is proposed in this paper. The
Dibyalekha Nayak +3 more
doaj +1 more source
HCM‐based indoor optical wireless communications: Timing and data recovery
IET Optoelectronics, Volume 17, Issue 5, Page 237-248, October 2023., 2023 A low‐complexity transceiver architecture for the HCM‐based communication links is proposed and a complete synchronisation procedure based on the spread‐spectrum techniques is presented. Bit error rate of the system is evaluated by Monte Carlo simulations, and effects of system parameters such as preamble length, fall and rise time of optical devices ...
Masoud Johar +3 more
wiley +1 more source
Time‐Efficient Object Recognition in Quantum Ghost Imaging
Advanced Quantum Technologies, Volume 6, Issue 2, February 2023., 2023 Acquiring information at the fastest possible rate is often desirable, particularly in quantum imaging which suffers from slow reconstruction speeds. Machine learning methods offer significant reduction in image acquisition times. Here, logistic regression shows a 10× speed up with a 99% prediction accuracy.
Chané Moodley +3 more
wiley +1 more source