Deep learning has emerged as a strong and efficient framework that can be applied to broad spectrum of complex problems which were difficult solve using the traditional machine techniques in past. In last few years, deep advanced radically such way it surpass human-level performance on number tasks. As consequence, is being extensively used most recent day-to-day applications. However, security systems are vulnerable crafted adversarial examples, may imperceptible human eye, but lead model...

Deep learning has evolved as a strong and efficient framework that can be applied to broad spectrum of complex problems which were difficult solve using the traditional machine techniques in past. The advancement deep been so radical today it surpass human-level performance. As consequence, is being extensively used most recent day-to-day applications. However, systems jeopardised by crafted adversarial samples, may imperceptible human eye, but lead model misclassify output. In times,...

The problem of answering questions about an image is popularly known as visual question (or VQA in short). It a well-established computer vision. However, none the methods currently utilize text often present image. These "texts images" provide additional useful cues and facilitate better understanding content. In this paper, we introduce novel task by reading images, i.e., optical character recognition or OCR. We refer to OCR-VQA. To systematic way studying new problem, large-scale dataset,...

Knowledge distillation deals with the problem of training a smaller model (Student) from high capacity source (Teacher) so as to retain most its performance. Existing approaches use either data or meta-data extracted it in order train Student. However, accessing dataset on which Teacher has been trained may not always be feasible if is very large poses privacy safety concerns (e.g., bio-metric medical data). Hence, this paper, we propose novel data-free method Student Teacher. Without even...

Text-based person search aims to retrieve the pedestrian images that best match a given text query. Existing methods utilize class-id information get discriminative and identity-preserving features. However, it is not well-explored whether beneficial explicitly ensure semantics of data are retained. In proposed work, we aim create semantics-preserving embeddings through an additional task attribute prediction. Since annotation typically unavailable in text-based search, first mine them from...

Text present in images are not merely strings, they provide useful cues about the image. Despite their utility better image understanding, scene texts used traditional visual question answering (VQA) models. In this work, we a VQA model which can read and perform reasoning on knowledge graph to arrive at an accurate answer. Our proposed has three mutually interacting modules: i. proposal module get word content proposals from image, ii. fusion fuse these proposals, base mine relevant facts,...

Estimation of 3D human pose from monocular image has gained considerable attention, as a key step to several human-centric applications. However, generalizability estimation models developed using supervision on large-scale in-studio datasets remains questionable, these often perform unsatisfactorily unseen in-the-wild environments. Though weakly-supervised have been proposed address this shortcoming, performance such relies availability paired some related task, 2D or multi-view pairs. In...

In this era of digital information explosion, an abundance data from numerous modalities is being generated as well archived everyday. However, most problems associated with training Deep Neural Networks still revolve around lack that rich enough for a given task. Data required not only initial model, but also future learning tasks such Model Compression and Incremental Learning. A diverse dataset may be used it feasible to store throughout the product life cycle due privacy issues or memory...

<div class="section abstract"><div class="htmlview paragraph">Light Detection and Ranging (LiDAR) is a promising type of sensor for autonomous driving that utilizes laser technology to provide perceptions accurate distance measurements obstacles in the vehicle path. In recent years, there has also been rise implementation LiDARs modern vehicles aid self-driving features. However, navigating adverse weather remains one biggest challenges achieving Level 5 full autonomy due...

ABSTRACT Hydraulically fractured shale reservoirs have facilitated studies of unexplored niches in the continental deep biosphere. In high-salinity North American systems, members genus Halanaerobium seem to be ubiquitous. Polymers like guar gum used as gelling agents hydraulic fracturing fluids are known fermentable substrates, but metabolic pathways encoding these processes not been characterized. To explore this, produced water samples from Permian Basin were incubated both at 30°C...

In this work, we find that controllable p‐type doping leads to Holstein‐type polarons in four electron‐rich two‐dimensional polymers (2DPs). Substoichometrically injecting holes into these 2DPs small optical bandgaps (<1.0 eV) and electrical conductivities (17 mS m‐1) significantly higher than their undoped analogs. Fourier‐transform infrared spectroscopy continuous‐wave electron paramagnetic resonance both reveal arises from the formation of polarons. We achieve maximal when comprised...

Existing data association techniques mostly focus on matching pairs of data-point sets and then repeating this process along space-time to achieve long term correspondences. However, in many problems such as person re-identification, a set data-points may be observed at multiple spatio-temporal locations and/or by agents network simply combining the local pairwise results between often leads inconsistencies over global horizons. In paper, we propose Novel Network Consistent Data Association...

The electronic structure of sodium tungsten bronzes, ${\mathrm{Na}}_{x}\mathrm{W}{\mathrm{O}}_{3}$, for full range $x$ is investigated by high-resolution angle-resolved photoemission spectroscopy (HR-ARPES). experimentally determined valence-band has been compared with the results ab initio band-structure calculation. HR-ARPES spectra taken in both insulating and metallic phase ${\mathrm{Na}}_{x}\mathrm{W}{\mathrm{O}}_{3}$ reveal origin metal-insulator transition (MIT) bronze system. In...

Regardless of the marvels brought by conventional frame‐based cameras, they have significant drawbacks due to their redundancy in data and temporal latency. This causes problem applications where low‐latency transmission high‐speed processing are mandatory. Proceeding along this line thought, neurobiological principles biological retina been adapted accomplish sparsity high dynamic range at pixel level. These bio‐inspired neuromorphic vision sensors alleviate more serious bottleneck...

In recent years, a new generation of low-power, neuromorphic, event-based vision sensors has been gaining popularity for their very low latency and data sparsity. Though the conventional frame-based cameras have advanced in lot ways, they suffer from redundancy temporal latency. The bio-inspired artificial retinas eliminate by capturing only change illumination at each pixel asynchronously communicating binary spikes. this work, we propose system to achieve task human activity recognition...

Knowledge Distillation is an effective method to transfer the learning across deep neural networks. Typically, dataset originally used for training Teacher model chosen as "Transfer Set" conduct knowledge Student. However, this original data may not always be freely available due privacy or sensitivity concerns. In such scenarios, existing approaches either iteratively compose a synthetic set representative of dataset, one sample at time learn generative set. both these involve complex...

We have carried out high-resolution angle-resolved photoemission spectroscopy (ARPES) to study the electronic structure of highly metallic ${\mathrm{Na}}_{x}\mathrm{W}{\mathrm{O}}_{3}$ ($x=0.58$, 0.65, 0.7, and 0.8). The experimentally determined valence-band has been compared with results an ab initio band-structure calculation. While presence impurity band (level) induced by Na doping is often invoked explain insulating state found at low concentrations, we find no signature in regime....