Srđan Stanković

University of Belgrade

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Miroslav Sokić

Institute for Technology of Nuclear and other Mineral Raw Materials

Branislav Marković

Institute for Technology of Nuclear and other Mineral Raw Materials

Irena Orović

University of Montenegro

Nela Petronijević

Institute for Technology of Nuclear and other Mineral Raw Materials

ŽK

Željko Kamberović

University of Belgrade

Axel Schippers

Federal Institute for Geosciences and Natural Resources

Miloš Pavlović

University of Belgrade

Dragana Radovanović

University of Belgrade

Miloš S. Stanković

Singidunum University

Ranko Petrović

University of Belgrade

Cooperative Institutions

University of Belgrade

Regulatory Agency for Electronic Communications and Postal Services

Ministry of Education, Science and Technological Development

Petal School District

Institute for Technology of Nuclear and other Mineral Raw Materials

Mining and Metallurgy Institute Bor

Institute of Chemistry, Technology and Metallurgy

Federal Institute for Geosciences and Natural Resources

University of Montenegro

University of Southampton

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Application of the Flotation Tailings as an Alternative Material for an Acid Mine Drainage Remediation: A Case Study of the Extremely Acidic Lake Robule (Serbia)

Metals (2019)

Nela Petronijević Srđan Stanković Dragana Radovanović Miroslav Sokić Branislav Marković

Flotation tailings rich in carbonate minerals from the tailings deposit of the copper mine Majdanpek (Serbia) were applied for neutralization of the water taken from the extremely acidic Lake Robule (Bor, Serbia). Tests conducted in Erlenmeyer flasks showed that after neutralization of the lake water to pH 7, over 99% of aluminum (Al), iron (Fe), and copper (Cu) precipitated, as well as 92% of Zn and 98% of Pb. In order to remove residual Mn and Ag, the water was further treated with NaOH. After treatment with NaOH, all concentrations of the metals in the lake water samples were below discharge limits for municipal wastewater according to the national legislation of the Republic of Serbia. The results of this work suggest that mining waste could be used for active neutralization of the acid mine drainage. The use of the mining waste instead of lime could reduce the costs of the active treatment of the acid mine drainage.

Acid Mine Drainage

10.3390/met10010016

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Citations (15)

Thermal Imagery Noise Influence on Face Recognition Performance

Ranko Petrović Branka Stojanović Miloš Pavlović Snežana Puzović Srđan Stanković

The utilization of a thermal band imaging sensor with aim to overcome the disadvantages of visible light face recognition systems, such as variation in lighting conditions, has become more popular in wide range of security and safety applications. Thermal imaging sensor enhances reliability of face recognition systems under different lighting conditions, including complete darkness. However, thermal imagery also possesses several disadvantages such as usual presence of noise, originating both from sensor and environment. This paper examines the influence of thermal imagery noise on face recognition performance in thermal-to-thermal face recognition applications.

10.1109/infoteh.2019.8717662

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Deep Features in Correlation Filters for Thermal Image Tracking

Milan Stojanović Nataša Vlahović Miloš S. Stanković Srđan Stanković

Object tracking using thermal infrared cameras has specific properties and challenges which distinguish it from the commonly used visual tracking. Recently, correlation filters (CF) based on deep features have been successfully applied in certain visual tracking scenarios. In this paper, we demonstrate that the success of these methods essentially depends on the way of how the deep features have been obtained. Indeed, the trackers based on CF and deep features use the pre-trained networks, originally trained for the object classification problem; hence, the obtained features are not invariant to changes of object appearance which may result from the change of camera type. We show that CF trackers based on deep features obtained from a convolutional architecture, pre-trained for visual object classification problem, have relatively poor performance when applied to the thermal tracking problem. Specifically, we test the performance of Kernelized Correlation Filter (KCF) on several chosen thermal video datasets, and demonstrate that the tracking results, when using simple feature representations (HOG features), are better than when using the pre-trained deep features. The results suggest that improved architectures and training methods for deep features should be developed in order to get more robust CF trackers.

BitTorrent tracker

Tracking (education)

Feature (linguistics)

10.1109/neurel.2018.8587030

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Fusion of Visual and Thermal Imagery for Illumination Invariant Face Recognition System

Miloš Pavlović Branka Stojanović Ranko Petrović Srđan Stanković

Visible light face recognition systems have been well researched and in controlled environments can reach excellent accuracy. Variation in lighting conditions results in performance degradation and illumination is the one of the major limitations in visible light face recognition systems. Using infrared facial images can provide a solution to this problem. Nearly invariant to changes in illumination, thermal IR imagery provides ability for recognition under all lighting conditions, including complete darkness. The system proposed in this paper takes advantages from both spectra and provides an effective algorithm for illumination invariant face recognition system.

Three-dimensional face recognition

10.1109/neurel.2018.8586985

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Real-Time Multi-Sensor Infrared Imagery Enhancement

Branka Stojanović Snežana Puzović Nataša Vlahović Ranko Petrović Srđan Stanković

Video enhancement algorithms in long-range multi-sensor surveillance systems are of great importance. Infrared sensors typically suffer from blur and noise originating from sensors and their environment. This paper proposes a real-time infrared imaging enhancement algorithm, applicable to multiple sensor types. The research presented in this paper is introductory for developing smart, adaptive, machine learning based enhancement systems.

10.1109/neurel.2018.8587023

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An adaptive notch filter with improved tracking properties

IEEE Transactions on Signal Processing (1995)

Marina V. Dragosevic Srđan Stanković

An analysis of the properties of an adaptive notch filter (ANF) applied to time-varying frequency tracking is presented. Starting from the derivation of an expression for ANF output power, asymptotically optimal values for the pole contraction and forgetting factors are derived for recursive prediction error (RPE) type ANF algorithms. Based on the obtained results, a new ANF algorithm that includes adaptation of both pole contraction and forgetting factors is proposed. The given experimental results confirm the theoretical conclusions and show that the proposed algorithm is highly efficient in practice.< >

Filtering theory

Tracking error

10.1109/78.414768

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Citations (76)

A Multifocal Study Investigation of Pyrolyzed Printed Circuit Board Leaching

Metals (2022)

Gvozden Jovanović Mladen Bugarčić Nela Petronijević Srečko Stopić Bernd Friedrich

Electric waste from numerous devices that are put out of use every day has some form of printed circuit board that contains precious and valuable metals in their components. In order to extract these metals, the printed circuit boards were crushed and pyrolyzed into powder. The fine pyrolyzed printed circuit board (PPCB) powder was separated into fractions, and the fine metallic fraction was used as a raw material for metal leaching extraction. In order to better understand how various metal species react in leaching media, several leaching agents were used (sulfuric acid, nitric acid, glycine, and acid mine drainage-AMD) alone, and with the addition of hydrogen peroxide. Additionally, the influence of the S/L ratio and leaching temperature were investigated in sulfuric acid leaching solutions, as this is the one most widely used. In one case, the reactor was heated in a thermal bath, while in the other, it was heated in an ultrasonic bath. Lastly, several experiments were conducted with a (consecutive) two-pronged leaching approach, with and without applied pretreatment. The aim of this paper is to give a multifocal and detailed approach to how metals such as Al, Cu, Co, Zn, Sn, and Ca behave when extracted from fine PPCB powder. However, some attention is given to Nd, Pd, Pb, and Ba as well. One of the main findings is that regardless of the pretreatment or the sequence of leaching media applied, consecutive two-pronged leaching cannot be used for selective metal extraction. However, AMD was found to be suitable for selective leaching with very limited applications.

Nitric acid

10.3390/met12122021

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Enhancement Algorithms for Low-Light and Low-Contrast Images

Snežana Puzović Ranko Petrović Miloš Pavlović Srđan Stanković

Images in bad weather can be degraded by scattering atmospheric particles, and suffer from low contrast and faint color. Main focus of this work is on dehazing methods that can be used for low-light and low-contrast conditions. Dehazing algorithms can be applied to low-light (night) imaging in a way that inverted night images are considered as hazy images. Different image quality metrics are used to measure quality of image enhancement algorithm. Since it is not easy to obtain original image without haze, special attention is given to the no-reference metrics that evaluate image contrast enhancement.

Haze

Contrast Enhancement

Diffuse sky radiation

10.1109/infoteh48170.2020.9066316

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Goethite dissolution by acidophilic bacteria

Frontiers in Microbiology (2024)

Srđan Stanković Axel Schippers

Previous studies have reported the role of some species of acidophilic bacteria in accelerating the dissolution of goethite under aerobic and anaerobic conditions. This has relevance for environments impacted by acid mine drainage and for the potential bioleaching of limonitic laterite ores. In this study, natural well-characterized goethite mineral samples and synthetic goethite were used in aerobic and anaerobic laboratory batch culture incubation experiments with ferric iron-reducing, acidophilic bacteria, including the lithoautotrophic species Acidithiobacillus (At.) thiooxidans , At. ferrooxidans, and At. caldus , as well as two strains of the organoheterotrophic species Acidiphilium cryptum . All bacteria remained alive throughout the experiments and efficiently reduced soluble ferric iron in solution in positive control assays. However, goethite dissolution was low to negligible in all experimental assays with natural goethite, while some dissolution occurred with synthetic goethite in agreement with previous publications. The results indicate that ferric iron-reducing microbial activity at low pH is less relevant for goethite dissolution than the oxidation of elemental sulfur to sulfuric acid. Microbial ferric iron reduction enhances but does not initiate goethite dissolution in very acidic liquors.

Iron bacteria

Acid Mine Drainage

Jarosite

10.3389/fmicb.2024.1360018

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Citations (1)

NEUREL 2018 Breaker Page

Branimir Reljin Jun Wang Program Chair Srđan Stanković Ana Gavrovska

10.1109/neurel.2018.8587022

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