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An energy-quality scalable (EQSCALE) feature extraction accelerator for IoT vision applications is presented. Knobs are introduced to dynamically adjust the tradeoff between energy and feature extraction quality, leveraging the intrinsic redundancy in video frames and the robustness of object recognition against missing features. Measurements of a testchip in 40nm show 310pJ/pixel energy at nominal...
The environmental sounds are usually classified by a convolutional neural network. However, there are few studies investigates the network input construction issue. In this paper, we investigate the impact of time resolution index of input spectrogram on classification performance. We want to verify whether the impact exists and quantify the impact. To this end, we adopt an efficient convolutional...
Chronic Obstructive Pulmonary Disease (COPD) is a persistent respiratory disease usually caused by toxic gases. The diagnosis is made by a specialist doctor on a report taken by a specialist technician using a spirometer. Diagnostic steps can only be carried out in hospital environment in the presence of a qualified technician. The diagnostic process is so troublesome that it leads to alternative...
Even though the various features of satirical language have been studied in computational linguistics, most of the research works have relied on the performance of the single machine learning algorithm. However, the implicit traits embedded in the language demand more certain, precise and accurate combination powers of an individual algorithm. In this study, we analyzed the performance of emotion-based...
This paper presents a novel method for interest level estimation based on matrix completion via rank minimization. The proposed method estimates interest levels of target objects from human behavior features which are extracted during selecting these objects. Specifically, by adopting matrix completion via rank minimization, unknown interest levels can be estimated. Furthermore, the proposed method...
A novel method to construct a network based on heterogeneous features obtained from music videos and social metadata for music video recommendation is presented in this paper. The proposed method enables construction of the network that can accurately associate users with music videos corresponding to their preference by the collaborative use of audio and textual features obtained from music videos...
A method for detecting human motion in complex scenarios based on Channel State Information (CSI) is presented. First, the sensitivity of CSI phase information to human motion is explored, especially to the strenuous motion. Through a large number of experiments, the influence of human motion on CSI phase is found out, and the characteristics of signal changes are extracted. The One-class Support...
Wearable and mobile medical devices provide efficient, comfortable, and economic health monitoring, having a wide range of applications from daily to clinical scenarios. Health data security becomes a critically important issue. Electrocardiogram (ECG) has proven to be a potential biometric in human recognition over the past decade. Unlike conventional authentication methods using passwords, fingerprints,...
An intrusion detection system (IDS) monitors the network traffic looking for suspicious or malicious activities or policy violations, which could represent an attack or unauthorized access. Traditional systems were designed to detect known attacks but cannot identify unknown threats. They most commonly detect known threats based on predefined rules or behavioral analysis through baselining the network...
One of the important problems in social media platforms like Twitter is the large number of social bots or sybil accounts which are controlled by automated agents, generally used for malicious activities. These include directing more visitors to certain websites which can be considered as spam, influence a community on a specific topic, spread misinformation, recruit people to illegal organizations,...
Speech analysis can be used for healthcare tasks such as pathology detection. Conventionally, a speech-language pathologist is specialized to detect anomalies from speech. Speech disorders result from a variety of causes such as brain injury, stroke, hearing loss, developmental delay or emotion alteration. Content of the speech is often not of interest for pathology detection, but characteristics...
VGG 16 and Inception-v3 networks were trained using a texture dataset of muddied and clean cows. A new dataset with 600 images that is similar to the actual texture dataset was introduced and used to train the networks. The method used to train the networks was transfer learning. ImageNet weights were trained using the similar dataset, then the newly trained weights were trained again using the actual...
Natural language processing methods are widely used to study the relationship between traditional Chinese medicine (TCM) prescriptions and diseases in textual data, and the results can discover the essence of TCM literature. In this paper, we get TCM treatment information from the abstract text at first by using the web crawlers. Second, the eigenvectors will be selected from the cleaned abstract...
WiFi-based Human activity recognition has attracted attention in the human-computer interaction, smart homes, and security monitoring fields. We first construct a WiFi-based activity dataset, namely WiAR, to provide a benchmark for existing works. Then, we leverage the moving variance of CSI to detect the start and end of activity. Moreover, we present K-means-based subcarrier selection mechanism...
We consider the problem of finding consistent matches across multiple images. Current state-of-the-art solutions use constraints on cycles of matches together with convex optimization, leading to computationally intensive iterative algorithms. In this paper, we instead propose a clustering-based formulation: we first rigorously show its equivalence with traditional approaches, and then propose QuickMatch,...
This paper presents a new method for video preference estimation using functional near-infrared spectroscopy signals (fNIRS signals). The proposed method first computes fNIRS features from fNIRS signals recorded while users are watching videos and multiple visual features from these videos. Next, by applying Locality Preserving Canonical Correlation Analysis to fNIRS features and each visual feature,...
Precision improvement of the classifiers is one of the main challenges for the Artificial Intelligence researchers. Feature weighting is one of the most common ideas in this area. In this study, in order to increase the accuracy of the K-Nearest Neighbors (KNN) classifier, a nonlinear feature weighting method based on the Spline interpolation is used. In this approach, a unique nonlinear function...
Searching sounds by text labels is often difficult, as text labels cannot always provide sufficient information for the sound content. Previously we proposed an unsupervised system called IMISOUND for sound search by vocal imitation. In this paper, we further propose a Convolutional Semi-Siamese Network (CSN) called IMINET. IMINET uses two towers of Convolutional Neural Networks (CNN) to extract features...
Ultrasound is one of the imaging modalities commonly used for detecting mass abnormalities of nodule. The observation of ultrasound images is conducted by the radiologists, which tend to be subjective. Therefore, the use of computer aided diagnosis (CADx) system based on image processing can assist the radiologists to give more objective decision-making for detecting the mass abnormalities of nodule...
Breast cancer is the leading cause of death in women worldwide. Ultrasonography (USG) is one of the imaging modalities which is widely used to detect and classify the mass abnormalities of the breast nodule. The use of image processing in the development a computer aided diagnosis (CADx) can assist the radiologists in analysing and interpreting the abnormalities of ultrasound nodules. This paper proposes...
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