Serwis Infona wykorzystuje pliki cookies (ciasteczka). Są to wartości tekstowe, zapamiętywane przez przeglądarkę na urządzeniu użytkownika. Nasz serwis ma dostęp do tych wartości oraz wykorzystuje je do zapamiętania danych dotyczących użytkownika, takich jak np. ustawienia (typu widok ekranu, wybór języka interfejsu), zapamiętanie zalogowania. Korzystanie z serwisu Infona oznacza zgodę na zapis informacji i ich wykorzystanie dla celów korzytania z serwisu. Więcej informacji można znaleźć w Polityce prywatności oraz Regulaminie serwisu. Zamknięcie tego okienka potwierdza zapoznanie się z informacją o plikach cookies, akceptację polityki prywatności i regulaminu oraz sposobu wykorzystywania plików cookies w serwisie. Możesz zmienić ustawienia obsługi cookies w swojej przeglądarce.
Abstract—In this paper, we analyse the use of Convolutional Neural Networks (CNNs or ConvNets) to discriminate vegetation species with few labelled samples. To the best of our knowledge, this is the first work dedicated to the investigation of the use of deep features in such task. The experimental evaluation demonstrate that deep features significantly outperform wellknown feature extraction techniques...
This paper presents a methodology for recognition of handwritten Marathi and English Characters-Numerals using shape context descriptor. During pre-processing an algorithm is developed to extract the Marathi and English Characters-Numerals form grid formatted datasheets. The corresponding sample points around the boundary of a character are computed. This is followed by obtaining the centroid of the...
Low Light Level Images (LLLIs) are captured with exceptionally low brightness and low contrast, and cannot be enhanced satisfactorily with ordinary methods. In this paper, we propose a LLLI enhancement method using coupled dictionary learning. During the training stage, a pair of dictionaries and a linear mapping function are learned simultaneously. The dictionary pair aims to describe the raw LLLIs...
In this paper we propose a new local learning based regression method which utilizes ensemble-learning as a form of regularization to reduce the variance of local estimators. This makes it possible to use local learning methods even with very high-dimensional datasets. The efficacy of the proposed method is illustrated on two publicly available high-dimensional sets in comparison with several global...
We model dyadic (two-person) interactions by discriminatively training a spatio-temporal deformable part model of fine-grained human interactions. All interactions involve at most two persons. Our models are capable of localizing human interactions in unsegmented videos, marking the interactions of interest in space and time. Our contributions are as follows: First, we create a model that localizes...
This paper deals with identifying a writer from his/her offline handwriting. In a multilingual country where a writer can scribe in multiple scripts, writer identification becomes challenging when we have individual handwriting data in one script while we need to verify/identify a writer from handwriting in another script. In this paper such an issue is addressed with two scripts: English and Bengali...
Human Epithelial type-2 (HEp-2) cells are used as substrates for the detection of Anti Nuclear Antibodies (ANA) in the Indirect Immunofluorescence (IIF) test to diagnose autoimmune diseases. Pathologists in the laboratory examine the IIF slides to detect and recognize theHEp-2 cell patterns to generate the report. So, the IIF test is subjective and requires objective analysis. This paper introduces...
Tattoos have been increasingly used as a discriminative soft biometric for people identification, such as criminal and victim identification in forensics investigation and law enforcement. However, automatic detection of tattoo images and accurate localization of the regions of interest are challenged by the large variations in artistic composition, color, shape, texture, location on the body, local...
Automatic classification of Human Epithelial Type-2 (HEp-2) specimen patterns is an important yet challenging problem in medical image analysis. Most prior works have primarily focused on cells images classification problem which is one of the early essential steps in the system pipeline, while less attention has been paid to the classification of whole-specimen ones. In this work, a specimen pattern...
Recognition of fruits automatically using machine vision is considered as challenging task as fruits exist in various colors, sizes, shapes and textures. Additionally, when images are acquired of them, variation is introduced due to imaging conditions also. In this paper we have recognized nine different classes of fruits. Fruit image dataset are obtained from web as well as certain images are acquired...
Imitation cartoon drawing is an important skill for cartoonists, requiring quantity of efforts on practising and guidance. In this paper, we propose EvaToon, an imitated drawing evaluate system, which automatically assigns judging scores and marks improper drawing regions. With our system, cartoonists can practise and get guidance by themselves. We have cooperated with several experts on developing...
The word embedding models are capable of capturing the semantic content of the textual words. The process of extracting a set of word embedding vectors from a text document is similar to the feature extraction step of the Bag-of-Features pipeline, which is usually used in computer vision tasks. That gives rise to the Bag-of-Embedded Words (BoEW) model. In this paper a novel learning technique that...
We propose a method to recognize pollen grains using a two-stage classifier. First, texture classification categorizes the pollen grains into sub-groups. Then, a final classification of individual pollen types is done by segmenting the image int multiple layers of regions for each pollen image. The main novelty in our method is threefold: (1) Adopting two successive classification stages. (2) Combining...
Considering the practical significances, handwriting recognition is getting an intense interest to the research community. Through, several studies have been conducted for Bengali handwriting recognition, a robust model for Bengali numerals classification is still due. Therefore, a hybrid model is presented in this paper, which aims to classify the Bengali numerals more precisely. The proposed model...
The proposed method aims to detect brain abnormality using bilateral symmetry property about the interhemispheric fissure (IHF) of human head scans. MRI brain has structural symmetry between the right cerebral hemisphere (RCH) and left cerebral hemisphere (LCH) of brain cerebrum. Any brain abnormalities due to tumors, hemorrhage, etc disturbs the similarity between the two hemispheres. We split the...
Target tracking is a challenging task in computer vision. It aims to detect and track particular objects in sequences. Illumination variation, motion of target, occlusion and background clutter make target tracking extremely challenging. We propose an novel online target tracking method which based on extreme learning machine(ELM). This tracking method consists of three modules: training, tracking...
This paper presents an automatic personalized photo recommender system which recommends photos from a large collection. Our proposed system recommends photos based on user-preferences about aesthetics and basic quality features of the photo. A large dataset is put together, which is used to collect user-preferences. A random forest based learning system has been employed to learn the user preferences...
Automatic restaurant attribute classification is an instance of multi-label learning. Users upload hundreds of photos along with textual reviews on websites like Yelp. The users also have the option of labelling the businesses with specific attributes such as if it is good for kids or if it has table service. In our work, we explore a variety of methods to label businesses with attributes using just...
This paper focuses in particular on the problem of Chinese characters recognition in natural scenes. Due to large variation in fonts, sizes, illumination, cluttered backgrounds, geometric distortions, etc., scene text recognition in the wild is a challenging problem. We proposed a novel method which based on Integral Channel Feature and pooling technology to extract informative features from scenes...
This paper proposed a new pedestrian detection method with depth information based on Histogram of Oriented Gradient and Support Vector Machin. According to the principle of perspective, use the different classifier with different scale in different position of the image to reduce the detection time. At the same time, Adding the Hard Examples to negative sample to decrease the false positive rate...
Podaj zakres dat dla filtrowania wyświetlonych wyników. Możesz podać datę początkową, końcową lub obie daty. Daty możesz wpisać ręcznie lub wybrać za pomocą kalendarza.