Reconstruction- and example-based super-resolution (SR) methods are promising for restoring a high-resolution (HR) image from low-resolution (LR) image(s). Under large magnification, reconstruction-based methods usually fail to hallucinate visual details while example-based methods sometimes introduce unexpected details. Given a generic LR image, to reconstruct a photo-realistic SR image and to suppress artifacts in the reconstructed SR image, we introduce a multi-scale dictionary to a novel SR method that simultaneously integrates local and non-local priors. The local prior suppresses artifacts by using steering kernel regression to predict the target pixel from a small local area. The non-local prior enriches visual details by taking a weighted average of a large neighborhood as an estimate of the target pixel. Essentially, these two priors are complementary to each other. Experimental results demonstrate that the proposed method can produce high quality SR recovery both quantitatively and perceptually.
标签： Super-resolution Multi-scale Dictionary Single Image for
上传时间： 2019-03-28
上传用户：fullout
C#远控源代码 * TCP network stream (IPv4 & IPv6 support) * Fast network serialization (NetSerializer) * Compressed (QuickLZ) & Encrypted (AES-128) communication * Multi-Threaded * UPnP Support * No-Ip.com Support * Visit Website (hidden & visible) * Show Messagebox * Task Manager * File Manager * Startup Manager * Remote Desktop * Remote Webcam * Remote Shell * Download & Execute * Upload & Execute * System Information * Computer Commands (Restart, Shutdown, Standby) * Keylogger (Unicode Support) * Reverse Proxy (SOCKS5) * Password Recovery (Common Browsers and FTP Clients) * Registry Editor
标签： QuasarRAT
上传时间： 2019-04-21
上传用户：netangels
Libsvm is a simple, easy-to-use, and efficient software for SVM classification and regression. It solves C-SVM classification, nu-SVM classification, one-class-SVM, epsilon-SVM regression, and nu-SVM regression. It also provides an automatic model selection tool for C-SVM classification.
标签： LibSVM
上传时间： 2019-06-09
上传用户：lyaiqing
In this paper we present a classifier called bi-density twin support vector machines (BDTWSVMs) for data classification. In the training stage, BDTWSVMs first compute the relative density degrees for all training points using the intra-class graph whose weights are determined by a local scaling heuristic strategy, then optimize a pair of nonparallel hyperplanes through two smaller sized support vector machine (SVM)-typed problems. In the prediction stage, BDTWSVMs assign to the class label depending on the kernel density degree-based distances from each test point to the two hyperplanes. BDTWSVMs not only inherit good properties from twin support vector machines (TWSVMs) but also give good description for data points. The experimental results on toy as well as publicly available datasets indicate that BDTWSVMs compare favorably with classical SVMs and TWSVMs in terms of generalization
标签： recognition Bi-density machines support pattern vector twin for
上传时间： 2019-06-09
上传用户：lyaiqing
在微电网调度过程中综合考虑经济、环境、蓄电池的 循环电量，建立多目标优化数学模型。针对传统多目标粒子 群算法(multi-objective particle swarm optimization，MOPSO) 的不足，提出引入模糊聚类分析的多目标粒子群算法 (multi-objective particle swarm optimization algorithm based on fuzzy clustering，FCMOPSO)，在迭代过程中引入模糊聚 类分析来寻找每代的集群最优解。与 MOPSO 相比， FCMOPSO 增强了算法的稳定性与全局搜索能力，同时使优 化结果中 Pareto 前沿分布更均匀。在求得 Pareto 最优解集 后，再根据各目标的重要程度，用模糊模型识别从最优解集 中找出不同情况下的最优方案。最后以一欧洲典型微电网为 例，验证算法的有效性和可行性。
上传时间： 2019-11-11
上传用户：Dr.赵劲帅
参照栈类模板的例子编写一个队列类模板class <T> Queue，私有成员包括：队首指针Front，队尾指针Tail，队列容积max。实现：构造函数Queue，复制构造函数Queue，析构函数~Queue，入队函数In，出队函数Out（每次出队，后面的元素自动前移一位），判队列空函数Empty。并分别用队列类模板定义int和double对象，通过实例调用各个成员函数。
标签： Queue 函数 double class Front Empty 队列 Tail 模板 Out
上传时间： 2020-05-04
上传用户：1qw2e3r4t5y6u7i8
New applications such as video conferencing, video on demand, multi- media transcoders, Voice-over-IP (VoIP), intrusion detection, distributed collaboration, and intranet security require advanced functionality from networks beyond simple forwarding congestion control techniques.
标签： Programmable Networks Active and
上传时间： 2020-05-26
上传用户：shancjb
Emerging technologies such as WiFi and WiMAX are profoundly changing the landscape of wireless broadband. As we evolve into future generation wireless networks, a primary challenge is the support of high data rate, integrated multi- media type traffic over a unified platform. Due to its inherent advantages in high-speed communication, orthogonal frequency division multiplexing (OFDM) has become the modem of choice for a number of high profile wireless systems (e.g., DVB-T, WiFi, WiMAX, Ultra-wideband).
标签： Broadband Wireless Networks
上传时间： 2020-05-26
上传用户：shancjb
Employing multiple transmit and receive antennas, namely using multi-input multi-output (MIMO) systems, has proven to be a major breakthrough in providing reliable wireless communication links. Since their invention in the mid-1990s, transmit diversity, achieved through space-time coding, and spatial multiplexing schemes have been the focus of much research in the area of wireless communications.
标签： Communication Systems Coding MIMO for
上传时间： 2020-05-26
上传用户：shancjb
Today’s wireless services have come a long way since the roll out of the conventional voice-centric cellular systems. The demand for wireless access in voice and high rate data multi-media applications has been increasing. New generation wireless communication systems are aimed at accommodating this demand through better resource management and improved transmission technologies.
标签： Radio Cognitive Software Defined
上传时间： 2020-05-26
上传用户：shancjb
